{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "uuid": "791458aa-147f-424c-881e-b4cb2371fb98"
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import warnings\n",
    "import os\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "warnings.filterwarnings('ignore')\n",
    "\"\"\"\n",
    "sns 相关设置\n",
    "@return:\n",
    "\"\"\"\n",
    "# 声明使用 Seaborn 样式\n",
    "sns.set()\n",
    "# 有五种seaborn的绘图风格，它们分别是：darkgrid, whitegrid, dark, white, ticks。默认的主题是darkgrid。\n",
    "sns.set_style(\"whitegrid\")\n",
    "# 有四个预置的环境，按大小从小到大排列分别为：paper, notebook, talk, poster。其中，notebook是默认的。\n",
    "sns.set_context('talk')\n",
    "# 中文字体设置-黑体\n",
    "plt.rcParams['font.sans-serif'] = ['SimHei']\n",
    "# 解决保存图像是负号'-'显示为方块的问题\n",
    "plt.rcParams['axes.unicode_minus'] = False\n",
    "# 解决Seaborn中文显示问题并调整字体大小\n",
    "sns.set(font='SimHei')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "uuid": "ec617675-ede6-4cf4-ade8-1bea8a51a659"
   },
   "outputs": [],
   "source": [
    "def reduce_mem_usage(df):\n",
    "    start_mem = df.memory_usage().sum() \n",
    "    print('Memory usage of dataframe is {:.2f} MB'.format(start_mem))\n",
    "    \n",
    "    for col in df.columns:\n",
    "        col_type = df[col].dtype\n",
    "        \n",
    "        if col_type != object:\n",
    "            c_min = df[col].min()\n",
    "            c_max = df[col].max()\n",
    "            if str(col_type)[:3] == 'int':\n",
    "                if c_min > np.iinfo(np.int8).min and c_max < np.iinfo(np.int8).max:\n",
    "                    df[col] = df[col].astype(np.int8)\n",
    "                elif c_min > np.iinfo(np.int16).min and c_max < np.iinfo(np.int16).max:\n",
    "                    df[col] = df[col].astype(np.int16)\n",
    "                elif c_min > np.iinfo(np.int32).min and c_max < np.iinfo(np.int32).max:\n",
    "                    df[col] = df[col].astype(np.int32)\n",
    "                elif c_min > np.iinfo(np.int64).min and c_max < np.iinfo(np.int64).max:\n",
    "                    df[col] = df[col].astype(np.int64)  \n",
    "            else:\n",
    "                if c_min > np.finfo(np.float16).min and c_max < np.finfo(np.float16).max:\n",
    "                    df[col] = df[col].astype(np.float16)\n",
    "                elif c_min > np.finfo(np.float32).min and c_max < np.finfo(np.float32).max:\n",
    "                    df[col] = df[col].astype(np.float32)\n",
    "                else:\n",
    "                    df[col] = df[col].astype(np.float64)\n",
    "        else:\n",
    "            df[col] = df[col].astype('category')\n",
    "\n",
    "    end_mem = df.memory_usage().sum() \n",
    "    print('Memory usage after optimization is: {:.2f} MB'.format(end_mem))\n",
    "    print('Decreased by {:.1f}%'.format(100 * (start_mem - end_mem) / start_mem))\n",
    "    \n",
    "    return df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "uuid": "d4a2de5e-2ef4-485d-bb99-455a9ac3595b",
    "tags": []
   },
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": "Memory usage of dataframe is 299089184.00 MB\nMemory usage after optimization is: 71521520.00 MB\nDecreased by 76.1%\n"
    }
   ],
   "source": [
    "# 读取数据\n",
    "data = pd.read_csv('./data_for_model.csv')\n",
    "y_train=pd.read_csv('./label_for_model.csv')\n",
    "data = reduce_mem_usage(data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "uuid": "7ce778f8-1a59-4b85-a167-faf5f971501e"
   },
   "outputs": [],
   "source": [
    "from sklearn.model_selection import KFold\n",
    "# 分离数据集，方便进行交叉验证\n",
    "X_train = data.loc[data['sample']=='train', :]\n",
    "X_test = data.loc[data['sample']=='test', :]\n",
    "y_train = y_train['isDefault']\n",
    "\n",
    "# 5折交叉验证\n",
    "folds = 5\n",
    "seed = 2020\n",
    "kf = KFold(n_splits=folds, shuffle=True, random_state=seed)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "uuid": "cfbc7926-d0c1-446d-a099-39c7549b5891",
    "tags": []
   },
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": "[LightGBM] [Warning] Unknown parameter: silent\nTraining until validation scores don't improve for 200 rounds\nEarly stopping, best iteration is:\n[293]\tvalid_0's auc: 0.731533\n"
    }
   ],
   "source": [
    "\"\"\"对训练集数据进行划分，分成训练集和验证集，并进行相应的操作\"\"\"\n",
    "from sklearn.model_selection import train_test_split\n",
    "import lightgbm as lgb\n",
    "# 数据集划分\n",
    "X_train_split, X_val, y_train_split, y_val = train_test_split(X_train, y_train, test_size=0.2)\n",
    "train_matrix = lgb.Dataset(X_train_split, label=y_train_split)\n",
    "valid_matrix = lgb.Dataset(X_val, label=y_val)\n",
    "\n",
    "params = {\n",
    "            'boosting_type': 'gbdt',\n",
    "            'objective': 'binary',\n",
    "            'learning_rate': 0.1,\n",
    "            'metric': 'auc',\n",
    "            'min_child_weight': 1e-3,\n",
    "            'num_leaves': 31,\n",
    "            'max_depth': -1,\n",
    "            'reg_lambda': 0,\n",
    "            'reg_alpha': 0,\n",
    "            'feature_fraction': 1,\n",
    "            'bagging_fraction': 1,\n",
    "            'bagging_freq': 0,\n",
    "            'seed': 2020,\n",
    "            'nthread': 8,\n",
    "            'silent': True,\n",
    "            'verbose': -1,\n",
    "}\n",
    "\n",
    "\"\"\"使用训练集数据进行模型训练\"\"\"\n",
    "model = lgb.train(params, train_set=train_matrix, valid_sets=valid_matrix, num_boost_round=20000, verbose_eval=1000, early_stopping_rounds=200)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "uuid": "bd92ba52-9828-4488-9f3f-57946399072f",
    "tags": []
   },
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": "未调参前lightgbm单模型在验证集上的AUC：0.7315329808218148\n"
    },
    {
     "output_type": "display_data",
     "data": {
      "text/plain": "<Figure size 576x576 with 1 Axes>",
      "image/svg+xml": "<?xml version=\"1.0\" encoding=\"utf-8\" standalone=\"no\"?>\r\n<!DOCTYPE svg PUBLIC \"-//W3C//DTD SVG 1.1//EN\"\r\n  \"http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd\">\r\n<!-- Created with matplotlib (https://matplotlib.org/) -->\r\n<svg height=\"495.7175pt\" version=\"1.1\" viewBox=\"0 0 508.8 495.7175\" width=\"508.8pt\" xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\">\r\n <metadata>\r\n  <rdf:RDF xmlns:cc=\"http://creativecommons.org/ns#\" xmlns:dc=\"http://purl.org/dc/elements/1.1/\" xmlns:rdf=\"http://www.w3.org/1999/02/22-rdf-syntax-ns#\">\r\n   <cc:Work>\r\n    <dc:type rdf:resource=\"http://purl.org/dc/dcmitype/StillImage\"/>\r\n    <dc:date>2020-09-25T12:36:44.548207</dc:date>\r\n    <dc:format>image/svg+xml</dc:format>\r\n    <dc:creator>\r\n     <cc:Agent>\r\n      <dc:title>Matplotlib v3.3.1, https://matplotlib.org/</dc:title>\r\n     </cc:Agent>\r\n    </dc:creator>\r\n   </cc:Work>\r\n  </rdf:RDF>\r\n </metadata>\r\n <defs>\r\n  <style type=\"text/css\">*{stroke-linecap:butt;stroke-linejoin:round;}</style>\r\n </defs>\r\n <g id=\"figure_1\">\r\n  <g id=\"patch_1\">\r\n   <path d=\"M 0 495.7175 \r\nL 508.8 495.7175 \r\nL 508.8 0 \r\nL 0 0 \r\nz\r\n\" style=\"fill:#ffffff;\"/>\r\n  </g>\r\n  <g id=\"axes_1\">\r\n   <g id=\"patch_2\">\r\n    <path d=\"M 46.95 456.33 \r\nL 493.35 456.33 \r\nL 493.35 21.45 \r\nL 46.95 21.45 \r\nz\r\n\" style=\"fill:#eaeaf2;\"/>\r\n   </g>\r\n   <g id=\"matplotlib.axis_1\">\r\n    <g id=\"xtick_1\">\r\n     <g id=\"line2d_1\">\r\n      <path clip-path=\"url(#pd79d4fe22e)\" d=\"M 46.95 456.33 \r\nL 46.95 21.45 \r\n\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;\"/>\r\n     </g>\r\n     <g id=\"text_1\">\r\n      <!-- 0.0 -->\r\n      <g style=\"fill:#262626;\" transform=\"translate(38.7 473.3925)scale(0.11 -0.11)\">\r\n       <defs>\r\n        <path d=\"M 3.125 29.296875 \r\nQ 3.90625 50 6.4375 56.046875 \r\nQ 8.984375 62.109375 13.671875 66.015625 \r\nQ 18.359375 69.921875 25.1875 69.921875 \r\nQ 32.03125 69.921875 37.109375 64.25 \r\nQ 42.1875 58.59375 43.75 50 \r\nQ 45.3125 41.40625 44.71875 30.265625 \r\nQ 44.140625 19.140625 40.8125 12.109375 \r\nQ 37.5 5.078125 30.859375 2.34375 \r\nQ 24.21875 -0.390625 17.578125 2.921875 \r\nQ 10.9375 6.25 8.203125 11.71875 \r\nQ 5.46875 17.1875 4.296875 23.234375 \r\nQ 3.125 29.296875 3.90625 50 \r\nz\r\nM 12.890625 52.734375 \r\nQ 10.546875 31.25 12.5 22.84375 \r\nQ 14.453125 14.453125 18.9375 10.9375 \r\nQ 23.4375 7.421875 28.125 9.5625 \r\nQ 32.8125 11.71875 34.953125 18.15625 \r\nQ 37.109375 24.609375 37.109375 32.21875 \r\nQ 37.109375 39.84375 36.515625 46.09375 \r\nQ 35.9375 52.34375 33 57.421875 \r\nQ 30.078125 62.5 25.1875 62.6875 \r\nQ 20.3125 62.890625 16.59375 57.8125 \r\nQ 12.890625 52.734375 10.546875 31.25 \r\nz\r\n\" id=\"SimHei-48\"/>\r\n        <path d=\"M 16.796875 1.953125 \r\nL 7.8125 1.953125 \r\nL 7.8125 10.546875 \r\nL 16.796875 10.546875 \r\nz\r\n\" id=\"SimHei-46\"/>\r\n       </defs>\r\n       <use xlink:href=\"#SimHei-48\"/>\r\n       <use x=\"50\" xlink:href=\"#SimHei-46\"/>\r\n       <use x=\"100\" xlink:href=\"#SimHei-48\"/>\r\n      </g>\r\n     </g>\r\n    </g>\r\n    <g id=\"xtick_2\">\r\n     <g id=\"line2d_2\">\r\n      <path clip-path=\"url(#pd79d4fe22e)\" d=\"M 136.23 456.33 \r\nL 136.23 21.45 \r\n\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;\"/>\r\n     </g>\r\n     <g id=\"text_2\">\r\n      <!-- 0.2 -->\r\n      <g style=\"fill:#262626;\" transform=\"translate(127.98 473.3925)scale(0.11 -0.11)\">\r\n       <defs>\r\n        <path d=\"M 4.6875 3.90625 \r\nQ 5.078125 9.765625 10.15625 14.453125 \r\nQ 15.234375 19.140625 23.046875 29.09375 \r\nQ 30.859375 39.0625 33.203125 44.53125 \r\nQ 35.546875 50 34.953125 53.90625 \r\nQ 34.375 57.8125 31.25 60.34375 \r\nQ 28.125 62.890625 24.015625 62.5 \r\nQ 19.921875 62.109375 16.203125 59.375 \r\nQ 12.5 56.640625 10.546875 51.171875 \r\nL 3.125 52.34375 \r\nQ 6.25 61.328125 11.125 65.421875 \r\nQ 16.015625 69.53125 22.65625 69.921875 \r\nQ 26.5625 70.3125 29.6875 69.71875 \r\nQ 32.8125 69.140625 36.125 66.984375 \r\nQ 39.453125 64.84375 41.59375 60.546875 \r\nQ 43.75 56.25 43.15625 50.1875 \r\nQ 42.578125 44.140625 37.109375 35.734375 \r\nQ 31.640625 27.34375 16.015625 9.375 \r\nL 44.140625 9.375 \r\nL 44.140625 2.34375 \r\nL 4.6875 2.34375 \r\nz\r\n\" id=\"SimHei-50\"/>\r\n       </defs>\r\n       <use xlink:href=\"#SimHei-48\"/>\r\n       <use x=\"50\" xlink:href=\"#SimHei-46\"/>\r\n       <use x=\"100\" xlink:href=\"#SimHei-50\"/>\r\n      </g>\r\n     </g>\r\n    </g>\r\n    <g id=\"xtick_3\">\r\n     <g id=\"line2d_3\">\r\n      <path clip-path=\"url(#pd79d4fe22e)\" d=\"M 225.51 456.33 \r\nL 225.51 21.45 \r\n\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;\"/>\r\n     </g>\r\n     <g id=\"text_3\">\r\n      <!-- 0.4 -->\r\n      <g style=\"fill:#262626;\" transform=\"translate(217.26 473.3925)scale(0.11 -0.11)\">\r\n       <defs>\r\n        <path d=\"M 31.25 17.1875 \r\nL 1.171875 17.1875 \r\nL 1.171875 23.828125 \r\nL 32.8125 69.53125 \r\nL 38.671875 69.53125 \r\nL 38.671875 23.828125 \r\nL 48.046875 23.828125 \r\nL 48.046875 17.1875 \r\nL 38.671875 17.1875 \r\nL 38.671875 2.34375 \r\nL 31.25 2.34375 \r\nz\r\nM 31.25 23.828125 \r\nL 31.25 54.6875 \r\nL 9.375 23.828125 \r\nz\r\n\" id=\"SimHei-52\"/>\r\n       </defs>\r\n       <use xlink:href=\"#SimHei-48\"/>\r\n       <use x=\"50\" xlink:href=\"#SimHei-46\"/>\r\n       <use x=\"100\" xlink:href=\"#SimHei-52\"/>\r\n      </g>\r\n     </g>\r\n    </g>\r\n    <g id=\"xtick_4\">\r\n     <g id=\"line2d_4\">\r\n      <path clip-path=\"url(#pd79d4fe22e)\" d=\"M 314.79 456.33 \r\nL 314.79 21.45 \r\n\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;\"/>\r\n     </g>\r\n     <g id=\"text_4\">\r\n      <!-- 0.6 -->\r\n      <g style=\"fill:#262626;\" transform=\"translate(306.54 473.3925)scale(0.11 -0.11)\">\r\n       <defs>\r\n        <path d=\"M 3.515625 19.53125 \r\nQ 4.296875 30.859375 6.046875 34.765625 \r\nQ 7.8125 38.671875 11.328125 44.53125 \r\nL 27.34375 69.53125 \r\nL 36.328125 69.53125 \r\nL 19.921875 43.75 \r\nQ 30.46875 46.484375 36.71875 42.96875 \r\nQ 42.96875 39.453125 45.109375 34.953125 \r\nQ 47.265625 30.46875 47.453125 25.1875 \r\nQ 47.65625 19.921875 45.890625 14.84375 \r\nQ 44.140625 9.765625 39.640625 5.65625 \r\nQ 35.15625 1.5625 27.140625 1.171875 \r\nQ 19.140625 0.78125 13.46875 4.09375 \r\nQ 7.8125 7.421875 5.65625 13.46875 \r\nQ 3.515625 19.53125 4.296875 30.859375 \r\nz\r\nM 12.5 16.015625 \r\nQ 19.53125 8.59375 25.390625 8.203125 \r\nQ 31.25 7.8125 35.15625 12.109375 \r\nQ 39.0625 16.40625 39.0625 24.609375 \r\nQ 39.0625 32.8125 34.171875 35.9375 \r\nQ 29.296875 39.0625 23.234375 38.28125 \r\nQ 17.1875 37.5 14.453125 32.421875 \r\nQ 11.71875 27.34375 12.109375 21.671875 \r\nQ 12.5 16.015625 19.53125 8.59375 \r\nz\r\n\" id=\"SimHei-54\"/>\r\n       </defs>\r\n       <use xlink:href=\"#SimHei-48\"/>\r\n       <use x=\"50\" xlink:href=\"#SimHei-46\"/>\r\n       <use x=\"100\" xlink:href=\"#SimHei-54\"/>\r\n      </g>\r\n     </g>\r\n    </g>\r\n    <g id=\"xtick_5\">\r\n     <g id=\"line2d_5\">\r\n      <path clip-path=\"url(#pd79d4fe22e)\" d=\"M 404.07 456.33 \r\nL 404.07 21.45 \r\n\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;\"/>\r\n     </g>\r\n     <g id=\"text_5\">\r\n      <!-- 0.8 -->\r\n      <g style=\"fill:#262626;\" transform=\"translate(395.82 473.3925)scale(0.11 -0.11)\">\r\n       <defs>\r\n        <path d=\"M 2.734375 16.796875 \r\nQ 2.734375 26.171875 5.078125 30.65625 \r\nQ 7.421875 35.15625 12.890625 37.890625 \r\nQ 8.203125 40.625 6.640625 43.9375 \r\nQ 5.078125 47.265625 4.875 51.5625 \r\nQ 4.6875 55.859375 6.046875 58.984375 \r\nQ 7.421875 62.109375 10.15625 64.84375 \r\nQ 12.890625 67.578125 16.203125 68.546875 \r\nQ 19.53125 69.53125 23.4375 69.53125 \r\nQ 27.34375 69.53125 30.46875 68.75 \r\nQ 33.59375 67.96875 37.109375 65.421875 \r\nQ 40.625 62.890625 42.1875 58.203125 \r\nQ 43.75 53.515625 41.984375 47.265625 \r\nQ 40.234375 41.015625 32.8125 37.5 \r\nQ 39.453125 35.546875 42.1875 31.4375 \r\nQ 44.921875 27.34375 44.921875 21.484375 \r\nQ 44.921875 15.625 43.15625 12.109375 \r\nQ 41.40625 8.59375 39.25 6.25 \r\nQ 37.109375 3.90625 33.390625 2.53125 \r\nQ 29.6875 1.171875 24.015625 1.171875 \r\nQ 18.359375 1.171875 14.25 2.53125 \r\nQ 10.15625 3.90625 7.421875 6.640625 \r\nQ 4.6875 9.375 3.703125 13.078125 \r\nQ 2.734375 16.796875 2.734375 26.171875 \r\nz\r\nM 10.9375 26.5625 \r\nQ 10.546875 17.1875 12.296875 13.671875 \r\nQ 14.0625 10.15625 18.75 9.171875 \r\nQ 23.4375 8.203125 28.515625 9.375 \r\nQ 33.59375 10.546875 35.546875 14.84375 \r\nQ 37.5 19.140625 36.90625 23.4375 \r\nQ 36.328125 27.734375 32.03125 30.65625 \r\nQ 27.734375 33.59375 22.65625 33.203125 \r\nQ 17.578125 32.8125 14.25 29.6875 \r\nQ 10.9375 26.5625 10.546875 17.1875 \r\nz\r\nM 12.109375 56.25 \r\nQ 12.109375 48.4375 14.84375 44.921875 \r\nQ 17.578125 41.40625 23.4375 41.40625 \r\nQ 29.296875 41.40625 32.21875 44.921875 \r\nQ 35.15625 48.4375 34.953125 53.3125 \r\nQ 34.765625 58.203125 31.4375 60.546875 \r\nQ 28.125 62.890625 22.453125 62.5 \r\nQ 16.796875 62.109375 14.453125 59.171875 \r\nQ 12.109375 56.25 12.109375 48.4375 \r\nz\r\n\" id=\"SimHei-56\"/>\r\n       </defs>\r\n       <use xlink:href=\"#SimHei-48\"/>\r\n       <use x=\"50\" xlink:href=\"#SimHei-46\"/>\r\n       <use x=\"100\" xlink:href=\"#SimHei-56\"/>\r\n      </g>\r\n     </g>\r\n    </g>\r\n    <g id=\"xtick_6\">\r\n     <g id=\"line2d_6\">\r\n      <path clip-path=\"url(#pd79d4fe22e)\" d=\"M 493.35 456.33 \r\nL 493.35 21.45 \r\n\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;\"/>\r\n     </g>\r\n     <g id=\"text_6\">\r\n      <!-- 1.0 -->\r\n      <g style=\"fill:#262626;\" transform=\"translate(485.1 473.3925)scale(0.11 -0.11)\">\r\n       <defs>\r\n        <path d=\"M 21.875 56.25 \r\nQ 16.796875 51.171875 8.984375 46.484375 \r\nL 8.984375 53.90625 \r\nQ 18.75 60.546875 25 69.53125 \r\nL 29.6875 69.53125 \r\nL 29.6875 2.34375 \r\nL 21.875 2.34375 \r\nz\r\n\" id=\"SimHei-49\"/>\r\n       </defs>\r\n       <use xlink:href=\"#SimHei-49\"/>\r\n       <use x=\"50\" xlink:href=\"#SimHei-46\"/>\r\n       <use x=\"100\" xlink:href=\"#SimHei-48\"/>\r\n      </g>\r\n     </g>\r\n    </g>\r\n    <g id=\"text_7\">\r\n     <!-- False Positive Rate -->\r\n     <g style=\"fill:#262626;\" transform=\"translate(213.15 487.0175)scale(0.12 -0.12)\">\r\n      <defs>\r\n       <path d=\"M 45.703125 61.328125 \r\nL 13.671875 61.328125 \r\nL 13.671875 39.453125 \r\nL 37.890625 39.453125 \r\nL 37.890625 32.03125 \r\nL 13.671875 32.03125 \r\nL 13.671875 1.953125 \r\nL 4.6875 1.953125 \r\nL 4.6875 68.75 \r\nL 45.703125 68.75 \r\nz\r\n\" id=\"SimHei-70\"/>\r\n       <path d=\"M 44.921875 1.953125 \r\nL 35.546875 1.953125 \r\nQ 34.765625 2.734375 34.375 4.09375 \r\nQ 33.984375 5.46875 33.984375 7.421875 \r\nQ 31.25 4.296875 27.34375 2.734375 \r\nQ 23.4375 1.171875 19.140625 1.171875 \r\nQ 12.890625 1.171875 8.59375 4.296875 \r\nQ 4.296875 7.421875 4.296875 13.28125 \r\nQ 4.296875 19.140625 8.203125 22.65625 \r\nQ 12.109375 26.171875 20.3125 27.34375 \r\nQ 25.78125 28.125 29.875 29.296875 \r\nQ 33.984375 30.46875 33.984375 32.421875 \r\nQ 33.984375 34.765625 32.21875 37.109375 \r\nQ 30.46875 39.453125 24.609375 39.453125 \r\nQ 19.921875 39.453125 17.765625 37.6875 \r\nQ 15.625 35.9375 14.84375 32.8125 \r\nL 6.25 32.8125 \r\nQ 7.03125 39.0625 11.90625 42.765625 \r\nQ 16.796875 46.484375 24.609375 46.484375 \r\nQ 33.203125 46.484375 37.5 42.578125 \r\nQ 41.796875 38.671875 41.796875 31.640625 \r\nL 41.796875 10.15625 \r\nQ 41.796875 7.8125 42.578125 5.859375 \r\nQ 43.359375 3.90625 44.921875 1.953125 \r\nz\r\nM 33.984375 16.40625 \r\nL 33.984375 24.21875 \r\nQ 31.640625 23.4375 29.484375 22.84375 \r\nQ 27.34375 22.265625 22.265625 21.484375 \r\nQ 16.40625 20.703125 14.640625 18.75 \r\nQ 12.890625 16.796875 12.890625 14.0625 \r\nQ 12.890625 11.71875 14.640625 9.953125 \r\nQ 16.40625 8.203125 19.921875 8.203125 \r\nQ 23.4375 8.203125 27.53125 10.15625 \r\nQ 31.640625 12.109375 33.984375 16.40625 \r\nz\r\n\" id=\"SimHei-97\"/>\r\n       <path d=\"M 28.515625 1.953125 \r\nL 20.703125 1.953125 \r\nL 20.703125 68.75 \r\nL 28.515625 68.75 \r\nz\r\n\" id=\"SimHei-108\"/>\r\n       <path d=\"M 42.96875 14.0625 \r\nQ 42.96875 7.8125 38.078125 4.484375 \r\nQ 33.203125 1.171875 25.78125 1.171875 \r\nQ 16.40625 1.171875 11.328125 4.875 \r\nQ 6.25 8.59375 6.25 15.625 \r\nL 14.0625 15.625 \r\nQ 14.0625 10.9375 17.375 9.375 \r\nQ 20.703125 7.8125 25.390625 7.8125 \r\nQ 30.078125 7.8125 32.421875 9.5625 \r\nQ 34.765625 11.328125 34.765625 14.0625 \r\nQ 34.765625 16.015625 32.8125 17.96875 \r\nQ 30.859375 19.921875 23.046875 21.09375 \r\nQ 14.0625 22.265625 10.734375 25.578125 \r\nQ 7.421875 28.90625 7.421875 34.375 \r\nQ 7.421875 39.0625 11.90625 42.765625 \r\nQ 16.40625 46.484375 25 46.484375 \r\nQ 32.8125 46.484375 37.296875 42.96875 \r\nQ 41.796875 39.453125 41.796875 33.59375 \r\nL 33.984375 33.59375 \r\nQ 33.984375 37.109375 31.4375 38.46875 \r\nQ 28.90625 39.84375 25 39.84375 \r\nQ 19.921875 39.84375 17.765625 38.078125 \r\nQ 15.625 36.328125 15.625 33.984375 \r\nQ 15.625 31.25 17.578125 29.6875 \r\nQ 19.53125 28.125 25.78125 27.34375 \r\nQ 35.9375 25.78125 39.453125 22.453125 \r\nQ 42.96875 19.140625 42.96875 14.0625 \r\nz\r\n\" id=\"SimHei-115\"/>\r\n       <path d=\"M 44.53125 16.796875 \r\nQ 43.75 9.765625 38.28125 5.46875 \r\nQ 32.8125 1.171875 25.390625 1.171875 \r\nQ 16.015625 1.171875 9.953125 7.21875 \r\nQ 3.90625 13.28125 3.90625 23.828125 \r\nQ 3.90625 34.375 9.953125 40.421875 \r\nQ 16.015625 46.484375 25.390625 46.484375 \r\nQ 33.59375 46.484375 38.859375 41.203125 \r\nQ 44.140625 35.9375 44.140625 23.828125 \r\nL 12.5 23.828125 \r\nQ 12.5 15.234375 16.203125 11.71875 \r\nQ 19.921875 8.203125 25.390625 8.203125 \r\nQ 29.6875 8.203125 32.421875 10.34375 \r\nQ 35.15625 12.5 35.9375 16.796875 \r\nz\r\nM 35.15625 30.078125 \r\nQ 34.375 35.546875 31.640625 37.6875 \r\nQ 28.90625 39.84375 24.609375 39.84375 \r\nQ 20.703125 39.84375 17.578125 37.6875 \r\nQ 14.453125 35.546875 12.890625 30.078125 \r\nz\r\n\" id=\"SimHei-101\"/>\r\n       <path id=\"SimHei-32\"/>\r\n       <path d=\"M 46.09375 48.4375 \r\nQ 46.09375 39.0625 40.625 33.59375 \r\nQ 35.15625 28.125 25.390625 28.125 \r\nL 14.0625 28.125 \r\nL 14.0625 1.953125 \r\nL 5.078125 1.953125 \r\nL 5.078125 68.75 \r\nL 25.390625 68.75 \r\nQ 35.15625 68.75 40.625 63.28125 \r\nQ 46.09375 57.8125 46.09375 48.4375 \r\nz\r\nM 37.109375 48.4375 \r\nQ 37.109375 55.859375 33.59375 58.59375 \r\nQ 30.078125 61.328125 23.046875 61.328125 \r\nL 14.0625 61.328125 \r\nL 14.0625 35.546875 \r\nL 23.046875 35.546875 \r\nQ 30.078125 35.546875 33.59375 38.28125 \r\nQ 37.109375 41.015625 37.109375 48.4375 \r\nz\r\n\" id=\"SimHei-80\"/>\r\n       <path d=\"M 45.703125 23.828125 \r\nQ 45.703125 13.671875 39.453125 7.421875 \r\nQ 33.203125 1.171875 24.609375 1.171875 \r\nQ 16.015625 1.171875 9.765625 7.421875 \r\nQ 3.515625 13.671875 3.515625 23.828125 \r\nQ 3.515625 33.984375 9.765625 40.234375 \r\nQ 16.015625 46.484375 24.609375 46.484375 \r\nQ 33.203125 46.484375 39.453125 40.234375 \r\nQ 45.703125 33.984375 45.703125 23.828125 \r\nz\r\nM 37.109375 23.828125 \r\nQ 37.109375 31.640625 33.203125 35.546875 \r\nQ 29.296875 39.453125 24.609375 39.453125 \r\nQ 19.921875 39.453125 16.015625 35.546875 \r\nQ 12.109375 31.640625 12.109375 23.828125 \r\nQ 12.109375 16.015625 16.015625 12.109375 \r\nQ 19.921875 8.203125 24.609375 8.203125 \r\nQ 29.296875 8.203125 33.203125 12.109375 \r\nQ 37.109375 16.015625 37.109375 23.828125 \r\nz\r\n\" id=\"SimHei-111\"/>\r\n       <path d=\"M 28.125 58.203125 \r\nL 20.3125 58.203125 \r\nL 20.3125 68.359375 \r\nL 28.125 68.359375 \r\nz\r\nM 28.125 1.953125 \r\nL 20.3125 1.953125 \r\nL 20.3125 45.703125 \r\nL 28.125 45.703125 \r\nz\r\n\" id=\"SimHei-105\"/>\r\n       <path d=\"M 42.96875 3.125 \r\nQ 41.015625 2.34375 38.46875 1.75 \r\nQ 35.9375 1.171875 31.640625 1.171875 \r\nQ 24.609375 1.171875 20.3125 5.078125 \r\nQ 16.015625 8.984375 16.015625 16.015625 \r\nL 16.015625 39.453125 \r\nL 2.734375 39.453125 \r\nL 2.734375 45.703125 \r\nL 16.015625 45.703125 \r\nL 16.015625 60.9375 \r\nL 23.828125 60.9375 \r\nL 23.828125 45.703125 \r\nL 39.84375 45.703125 \r\nL 39.84375 39.453125 \r\nL 23.828125 39.453125 \r\nL 23.828125 15.625 \r\nQ 23.828125 12.5 25.390625 10.34375 \r\nQ 26.953125 8.203125 31.25 8.203125 \r\nQ 35.546875 8.203125 38.28125 8.984375 \r\nQ 41.015625 9.765625 42.96875 10.9375 \r\nz\r\n\" id=\"SimHei-116\"/>\r\n       <path d=\"M 44.921875 45.703125 \r\nL 28.515625 1.171875 \r\nL 19.921875 1.171875 \r\nL 3.515625 45.703125 \r\nL 11.71875 45.703125 \r\nL 23.828125 11.71875 \r\nL 24.609375 11.71875 \r\nL 36.71875 45.703125 \r\nz\r\n\" id=\"SimHei-118\"/>\r\n       <path d=\"M 46.875 1.953125 \r\nL 37.5 1.953125 \r\nL 23.4375 30.859375 \r\nL 13.28125 30.859375 \r\nL 13.28125 1.953125 \r\nL 4.296875 1.953125 \r\nL 4.296875 68.75 \r\nL 23.828125 68.75 \r\nQ 33.203125 68.75 39.0625 64.25 \r\nQ 44.921875 59.765625 44.921875 49.609375 \r\nQ 44.921875 41.796875 41.015625 37.5 \r\nQ 37.109375 33.203125 32.03125 32.03125 \r\nz\r\nM 35.9375 49.609375 \r\nQ 35.9375 55.078125 32.609375 58.203125 \r\nQ 29.296875 61.328125 21.875 61.328125 \r\nL 13.28125 61.328125 \r\nL 13.28125 38.28125 \r\nL 24.21875 38.28125 \r\nQ 28.90625 38.28125 32.421875 40.8125 \r\nQ 35.9375 43.359375 35.9375 49.609375 \r\nz\r\n\" id=\"SimHei-82\"/>\r\n      </defs>\r\n      <use xlink:href=\"#SimHei-70\"/>\r\n      <use x=\"50\" xlink:href=\"#SimHei-97\"/>\r\n      <use x=\"100\" xlink:href=\"#SimHei-108\"/>\r\n      <use x=\"150\" xlink:href=\"#SimHei-115\"/>\r\n      <use x=\"200\" xlink:href=\"#SimHei-101\"/>\r\n      <use x=\"250\" xlink:href=\"#SimHei-32\"/>\r\n      <use x=\"300\" xlink:href=\"#SimHei-80\"/>\r\n      <use x=\"350\" xlink:href=\"#SimHei-111\"/>\r\n      <use x=\"400\" xlink:href=\"#SimHei-115\"/>\r\n      <use x=\"450\" xlink:href=\"#SimHei-105\"/>\r\n      <use x=\"500\" xlink:href=\"#SimHei-116\"/>\r\n      <use x=\"550\" xlink:href=\"#SimHei-105\"/>\r\n      <use x=\"600\" xlink:href=\"#SimHei-118\"/>\r\n      <use x=\"650\" xlink:href=\"#SimHei-101\"/>\r\n      <use x=\"700\" xlink:href=\"#SimHei-32\"/>\r\n      <use x=\"750\" xlink:href=\"#SimHei-82\"/>\r\n      <use x=\"800\" xlink:href=\"#SimHei-97\"/>\r\n      <use x=\"850\" xlink:href=\"#SimHei-116\"/>\r\n      <use x=\"900\" xlink:href=\"#SimHei-101\"/>\r\n     </g>\r\n    </g>\r\n   </g>\r\n   <g id=\"matplotlib.axis_2\">\r\n    <g id=\"ytick_1\">\r\n     <g id=\"line2d_7\">\r\n      <path clip-path=\"url(#pd79d4fe22e)\" d=\"M 46.95 456.33 \r\nL 493.35 456.33 \r\n\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;\"/>\r\n     </g>\r\n     <g id=\"text_8\">\r\n      <!-- 0.0 -->\r\n      <g style=\"fill:#262626;\" transform=\"translate(20.95 460.11125)scale(0.11 -0.11)\">\r\n       <use xlink:href=\"#SimHei-48\"/>\r\n       <use x=\"50\" xlink:href=\"#SimHei-46\"/>\r\n       <use x=\"100\" xlink:href=\"#SimHei-48\"/>\r\n      </g>\r\n     </g>\r\n    </g>\r\n    <g id=\"ytick_2\">\r\n     <g id=\"line2d_8\">\r\n      <path clip-path=\"url(#pd79d4fe22e)\" d=\"M 46.95 369.354 \r\nL 493.35 369.354 \r\n\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;\"/>\r\n     </g>\r\n     <g id=\"text_9\">\r\n      <!-- 0.2 -->\r\n      <g style=\"fill:#262626;\" transform=\"translate(20.95 373.13525)scale(0.11 -0.11)\">\r\n       <use xlink:href=\"#SimHei-48\"/>\r\n       <use x=\"50\" xlink:href=\"#SimHei-46\"/>\r\n       <use x=\"100\" xlink:href=\"#SimHei-50\"/>\r\n      </g>\r\n     </g>\r\n    </g>\r\n    <g id=\"ytick_3\">\r\n     <g id=\"line2d_9\">\r\n      <path clip-path=\"url(#pd79d4fe22e)\" d=\"M 46.95 282.378 \r\nL 493.35 282.378 \r\n\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;\"/>\r\n     </g>\r\n     <g id=\"text_10\">\r\n      <!-- 0.4 -->\r\n      <g style=\"fill:#262626;\" transform=\"translate(20.95 286.15925)scale(0.11 -0.11)\">\r\n       <use xlink:href=\"#SimHei-48\"/>\r\n       <use x=\"50\" xlink:href=\"#SimHei-46\"/>\r\n       <use x=\"100\" xlink:href=\"#SimHei-52\"/>\r\n      </g>\r\n     </g>\r\n    </g>\r\n    <g id=\"ytick_4\">\r\n     <g id=\"line2d_10\">\r\n      <path clip-path=\"url(#pd79d4fe22e)\" d=\"M 46.95 195.402 \r\nL 493.35 195.402 \r\n\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;\"/>\r\n     </g>\r\n     <g id=\"text_11\">\r\n      <!-- 0.6 -->\r\n      <g style=\"fill:#262626;\" transform=\"translate(20.95 199.18325)scale(0.11 -0.11)\">\r\n       <use xlink:href=\"#SimHei-48\"/>\r\n       <use x=\"50\" xlink:href=\"#SimHei-46\"/>\r\n       <use x=\"100\" xlink:href=\"#SimHei-54\"/>\r\n      </g>\r\n     </g>\r\n    </g>\r\n    <g id=\"ytick_5\">\r\n     <g id=\"line2d_11\">\r\n      <path clip-path=\"url(#pd79d4fe22e)\" d=\"M 46.95 108.426 \r\nL 493.35 108.426 \r\n\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;\"/>\r\n     </g>\r\n     <g id=\"text_12\">\r\n      <!-- 0.8 -->\r\n      <g style=\"fill:#262626;\" transform=\"translate(20.95 112.20725)scale(0.11 -0.11)\">\r\n       <use xlink:href=\"#SimHei-48\"/>\r\n       <use x=\"50\" xlink:href=\"#SimHei-46\"/>\r\n       <use x=\"100\" xlink:href=\"#SimHei-56\"/>\r\n      </g>\r\n     </g>\r\n    </g>\r\n    <g id=\"ytick_6\">\r\n     <g id=\"line2d_12\">\r\n      <path clip-path=\"url(#pd79d4fe22e)\" d=\"M 46.95 21.45 \r\nL 493.35 21.45 \r\n\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;\"/>\r\n     </g>\r\n     <g id=\"text_13\">\r\n      <!-- 1.0 -->\r\n      <g style=\"fill:#262626;\" transform=\"translate(20.95 25.23125)scale(0.11 -0.11)\">\r\n       <use xlink:href=\"#SimHei-49\"/>\r\n       <use x=\"50\" xlink:href=\"#SimHei-46\"/>\r\n       <use x=\"100\" xlink:href=\"#SimHei-48\"/>\r\n      </g>\r\n     </g>\r\n    </g>\r\n    <g id=\"text_14\">\r\n     <!-- True Positive Rate -->\r\n     <g style=\"fill:#262626;\" transform=\"translate(15.45 292.89)rotate(-90)scale(0.12 -0.12)\">\r\n      <defs>\r\n       <path d=\"M 44.53125 61.328125 \r\nL 28.90625 61.328125 \r\nL 28.90625 1.953125 \r\nL 19.921875 1.953125 \r\nL 19.921875 61.328125 \r\nL 4.296875 61.328125 \r\nL 4.296875 68.75 \r\nL 44.53125 68.75 \r\nz\r\n\" id=\"SimHei-84\"/>\r\n       <path d=\"M 39.0625 37.890625 \r\nQ 31.640625 39.0625 26.5625 35.734375 \r\nQ 21.484375 32.421875 17.96875 24.21875 \r\nL 17.96875 1.953125 \r\nL 10.15625 1.953125 \r\nL 10.15625 45.703125 \r\nL 17.96875 45.703125 \r\nL 17.96875 34.375 \r\nQ 21.484375 40.625 26.75 43.546875 \r\nQ 32.03125 46.484375 39.0625 46.484375 \r\nz\r\n\" id=\"SimHei-114\"/>\r\n       <path d=\"M 43.75 1.953125 \r\nL 35.9375 1.953125 \r\nL 35.9375 10.15625 \r\nQ 32.8125 5.859375 29.09375 3.515625 \r\nQ 25.390625 1.171875 19.53125 1.171875 \r\nQ 12.5 1.171875 8.984375 5.078125 \r\nQ 5.46875 8.984375 5.46875 14.84375 \r\nL 5.46875 45.703125 \r\nL 13.28125 45.703125 \r\nL 13.28125 17.578125 \r\nQ 13.28125 12.890625 15.625 10.15625 \r\nQ 17.96875 7.421875 21.875 7.421875 \r\nQ 26.953125 7.421875 31.4375 12.6875 \r\nQ 35.9375 17.96875 35.9375 25.78125 \r\nL 35.9375 45.703125 \r\nL 43.75 45.703125 \r\nz\r\n\" id=\"SimHei-117\"/>\r\n      </defs>\r\n      <use xlink:href=\"#SimHei-84\"/>\r\n      <use x=\"50\" xlink:href=\"#SimHei-114\"/>\r\n      <use x=\"100\" xlink:href=\"#SimHei-117\"/>\r\n      <use x=\"150\" xlink:href=\"#SimHei-101\"/>\r\n      <use x=\"200\" xlink:href=\"#SimHei-32\"/>\r\n      <use x=\"250\" xlink:href=\"#SimHei-80\"/>\r\n      <use x=\"300\" xlink:href=\"#SimHei-111\"/>\r\n      <use x=\"350\" xlink:href=\"#SimHei-115\"/>\r\n      <use x=\"400\" xlink:href=\"#SimHei-105\"/>\r\n      <use x=\"450\" xlink:href=\"#SimHei-116\"/>\r\n      <use x=\"500\" xlink:href=\"#SimHei-105\"/>\r\n      <use x=\"550\" xlink:href=\"#SimHei-118\"/>\r\n      <use x=\"600\" xlink:href=\"#SimHei-101\"/>\r\n      <use x=\"650\" xlink:href=\"#SimHei-32\"/>\r\n      <use x=\"700\" xlink:href=\"#SimHei-82\"/>\r\n      <use x=\"750\" xlink:href=\"#SimHei-97\"/>\r\n      <use x=\"800\" xlink:href=\"#SimHei-116\"/>\r\n      <use x=\"850\" xlink:href=\"#SimHei-101\"/>\r\n     </g>\r\n    </g>\r\n   </g>\r\n   <g id=\"line2d_13\">\r\n    <path clip-path=\"url(#pd79d4fe22e)\" d=\"M 46.95 456.33 \r\nL 47.053879 454.440892 \r\nL 47.080978 454.349188 \r\nL 47.184857 453.046987 \r\nL 47.230022 452.936942 \r\nL 47.333901 452.03824 \r\nL 47.361 451.964877 \r\nL 47.460362 451.084516 \r\nL 47.482945 451.029493 \r\nL 47.59134 450.295859 \r\nL 47.622956 450.185814 \r\nL 47.731351 449.598906 \r\nL 47.744901 449.488861 \r\nL 47.853296 448.480114 \r\nL 47.866846 448.370069 \r\nL 47.970725 447.379663 \r\nL 47.988791 447.287959 \r\nL 48.09267 446.24253 \r\nL 48.119769 446.150826 \r\nL 48.228164 445.288806 \r\nL 48.250747 445.197101 \r\nL 48.354626 444.31674 \r\nL 48.377208 444.225036 \r\nL 48.481087 443.363016 \r\nL 48.50367 443.289652 \r\nL 48.612065 442.5927 \r\nL 48.65723 442.500996 \r\nL 48.765626 441.895748 \r\nL 48.779175 441.840725 \r\nL 48.887571 441.437226 \r\nL 48.923702 441.327181 \r\nL 49.027581 440.685251 \r\nL 49.063713 440.593547 \r\nL 49.172109 439.511436 \r\nL 49.208241 439.401391 \r\nL 49.316636 438.869507 \r\nL 49.321153 438.869507 \r\nL 49.429548 437.897441 \r\nL 49.46568 437.824078 \r\nL 49.574076 436.980399 \r\nL 49.601175 436.907035 \r\nL 49.700537 436.210083 \r\nL 49.732153 436.191742 \r\nL 49.840548 435.403085 \r\nL 49.912812 435.29304 \r\nL 50.021207 434.467701 \r\nL 50.04379 434.375997 \r\nL 50.138636 433.78909 \r\nL 50.188317 433.679045 \r\nL 50.296713 433.073797 \r\nL 50.337361 432.963751 \r\nL 50.436724 432.395185 \r\nL 50.504471 432.28514 \r\nL 50.612867 431.624869 \r\nL 50.635449 431.533165 \r\nL 50.743844 431.00128 \r\nL 50.766427 430.927917 \r\nL 50.874822 430.285987 \r\nL 50.901921 430.212623 \r\nL 51.010317 429.607375 \r\nL 51.059998 429.515671 \r\nL 51.163877 428.837059 \r\nL 51.209042 428.745355 \r\nL 51.312921 428.286834 \r\nL 51.358086 428.176788 \r\nL 51.452932 427.736608 \r\nL 51.480031 427.699926 \r\nL 51.588427 427.113019 \r\nL 51.633591 427.021315 \r\nL 51.741987 426.416066 \r\nL 51.755536 426.306021 \r\nL 51.863932 425.810818 \r\nL 51.922646 425.700773 \r\nL 52.003943 425.297274 \r\nL 52.058141 425.187229 \r\nL 52.143954 424.912116 \r\nL 52.211701 424.802071 \r\nL 52.31558 424.435254 \r\nL 52.347195 424.34355 \r\nL 52.451074 423.738302 \r\nL 52.491723 423.628257 \r\nL 52.591085 423.078031 \r\nL 52.667866 422.967986 \r\nL 52.771745 422.399419 \r\nL 52.785294 422.399419 \r\nL 52.884657 421.849194 \r\nL 52.916272 421.757489 \r\nL 53.002085 421.280627 \r\nL 53.060799 421.225605 \r\nL 53.155646 420.583675 \r\nL 53.182744 420.49197 \r\nL 53.277591 420.05179 \r\nL 53.331788 419.978426 \r\nL 53.435667 419.18977 \r\nL 53.467283 419.079725 \r\nL 53.575678 418.32775 \r\nL 53.620843 418.236045 \r\nL 53.720206 417.869228 \r\nL 53.801502 417.759183 \r\nL 53.900865 417.374025 \r\nL 53.936997 417.337343 \r\nL 54.045392 416.677073 \r\nL 54.072491 416.567028 \r\nL 54.162821 416.20021 \r\nL 54.230568 416.090165 \r\nL 54.325414 415.631644 \r\nL 54.34348 415.631644 \r\nL 54.451876 415.191463 \r\nL 54.478975 415.136441 \r\nL 54.58737 414.641238 \r\nL 54.605436 414.531193 \r\nL 54.695766 413.980967 \r\nL 54.736414 413.870922 \r\nL 54.817711 413.19231 \r\nL 54.889975 413.082265 \r\nL 54.993854 412.642085 \r\nL 55.057084 412.568721 \r\nL 55.160963 411.963473 \r\nL 55.201612 411.871769 \r\nL 55.310007 411.174816 \r\nL 55.355172 411.064771 \r\nL 55.450018 410.624591 \r\nL 55.522282 410.514546 \r\nL 55.617128 410.294455 \r\nL 55.680359 410.18441 \r\nL 55.788754 409.835934 \r\nL 55.824886 409.725889 \r\nL 55.933282 409.340731 \r\nL 55.98748 409.285708 \r\nL 56.095875 408.643778 \r\nL 56.136523 408.570415 \r\nL 56.244919 407.983508 \r\nL 56.285567 407.965167 \r\nL 56.393963 407.3966 \r\nL 56.425578 407.341578 \r\nL 56.529457 406.626284 \r\nL 56.574622 406.516239 \r\nL 56.678501 406.204445 \r\nL 56.737215 406.0944 \r\nL 56.845611 405.617537 \r\nL 56.890776 405.507492 \r\nL 56.994655 405.232379 \r\nL 57.030787 405.159016 \r\nL 57.134666 404.535427 \r\nL 57.166281 404.480404 \r\nL 57.274677 403.930179 \r\nL 57.324358 403.820134 \r\nL 57.419204 403.343271 \r\nL 57.455336 403.269908 \r\nL 57.563732 402.66466 \r\nL 57.595347 402.572956 \r\nL 57.699226 402.297843 \r\nL 57.721808 402.24282 \r\nL 57.803105 401.80264 \r\nL 57.875369 401.692595 \r\nL 57.983764 401.197392 \r\nL 58.019896 401.105687 \r\nL 58.128292 400.610484 \r\nL 58.159907 400.51878 \r\nL 58.263786 400.115281 \r\nL 58.281852 400.060259 \r\nL 58.390248 399.895191 \r\nL 58.42638 399.785146 \r\nL 58.530259 399.198238 \r\nL 58.593489 399.088193 \r\nL 58.688335 398.648013 \r\nL 58.742533 398.556308 \r\nL 58.850929 398.079446 \r\nL 58.986423 397.969401 \r\nL 59.094819 397.602584 \r\nL 59.15805 397.492539 \r\nL 59.266445 396.960654 \r\nL 59.320643 396.86895 \r\nL 59.424522 396.392088 \r\nL 59.501302 396.282043 \r\nL 59.609698 395.988589 \r\nL 59.641313 395.896885 \r\nL 59.745192 395.640113 \r\nL 59.78584 395.548408 \r\nL 59.894236 395.218273 \r\nL 59.957467 395.126569 \r\nL 60.065862 394.704729 \r\nL 60.151675 394.594684 \r\nL 60.255555 394.007777 \r\nL 60.296203 393.916072 \r\nL 60.400082 393.640959 \r\nL 60.427181 393.549255 \r\nL 60.535576 393.01737 \r\nL 60.585258 392.907325 \r\nL 60.689137 392.57719 \r\nL 60.738818 392.467145 \r\nL 60.829148 392.302077 \r\nL 60.892378 392.192032 \r\nL 60.996258 391.880237 \r\nL 61.059488 391.770192 \r\nL 61.167884 391.458398 \r\nL 61.226598 391.348353 \r\nL 61.334994 390.816468 \r\nL 61.366609 390.706423 \r\nL 61.470488 390.43131 \r\nL 61.520169 390.321265 \r\nL 61.628565 390.119515 \r\nL 61.67373 390.00947 \r\nL 61.782125 389.716017 \r\nL 61.804708 389.624312 \r\nL 61.908587 389.220814 \r\nL 61.976334 389.14745 \r\nL 62.080213 388.835656 \r\nL 62.120861 388.72561 \r\nL 62.22474 388.230407 \r\nL 62.278938 388.120362 \r\nL 62.382817 387.881931 \r\nL 62.423466 387.771886 \r\nL 62.527345 387.515114 \r\nL 62.57251 387.441751 \r\nL 62.671872 387.111615 \r\nL 62.753169 387.00157 \r\nL 62.857048 386.56139 \r\nL 62.951894 386.451345 \r\nL 63.06029 386.194573 \r\nL 63.159652 386.084527 \r\nL 63.249982 385.791074 \r\nL 63.353861 385.681029 \r\nL 63.448707 385.424257 \r\nL 63.520971 385.332552 \r\nL 63.62485 384.910713 \r\nL 63.710663 384.800668 \r\nL 63.819058 384.6356 \r\nL 63.85519 384.543896 \r\nL 63.950036 384.067033 \r\nL 64.004234 383.956988 \r\nL 64.103597 383.406763 \r\nL 64.148762 383.296718 \r\nL 64.243608 382.874878 \r\nL 64.333937 382.764833 \r\nL 64.437816 382.563083 \r\nL 64.473948 382.453038 \r\nL 64.582344 381.866131 \r\nL 64.654608 381.756086 \r\nL 64.75397 381.352587 \r\nL 64.803651 381.242542 \r\nL 64.903014 380.710657 \r\nL 64.961728 380.600612 \r\nL 65.065607 380.288817 \r\nL 65.106256 380.178772 \r\nL 65.192069 379.866978 \r\nL 65.237234 379.811955 \r\nL 65.341113 379.426797 \r\nL 65.363695 379.335093 \r\nL 65.472091 379.115003 \r\nL 65.503706 379.004958 \r\nL 65.612102 378.693163 \r\nL 65.625651 378.656481 \r\nL 65.734047 378.271323 \r\nL 65.801794 378.161278 \r\nL 65.910189 377.666075 \r\nL 65.964387 377.55603 \r\nL 66.06375 377.189213 \r\nL 66.126981 377.079168 \r\nL 66.226343 376.638987 \r\nL 66.303123 376.528942 \r\nL 66.397969 375.868672 \r\nL 66.447651 375.795308 \r\nL 66.556046 375.465173 \r\nL 66.569596 375.428491 \r\nL 66.677991 374.914947 \r\nL 66.700574 374.804902 \r\nL 66.804453 374.54813 \r\nL 66.840585 374.474767 \r\nL 66.94898 373.924541 \r\nL 67.016727 373.851178 \r\nL 67.125123 373.521042 \r\nL 67.188354 373.410997 \r\nL 67.296749 373.245929 \r\nL 67.387079 373.135884 \r\nL 67.495474 372.842431 \r\nL 67.509024 372.750726 \r\nL 67.612903 372.438932 \r\nL 67.644518 372.347227 \r\nL 67.743881 371.98041 \r\nL 67.816145 371.870365 \r\nL 67.901958 371.650275 \r\nL 67.969705 371.558571 \r\nL 68.078101 371.136731 \r\nL 68.136815 371.026686 \r\nL 68.236177 370.769914 \r\nL 68.276826 370.696551 \r\nL 68.385221 370.238029 \r\nL 68.457485 370.127984 \r\nL 68.556848 369.889553 \r\nL 68.606529 369.779508 \r\nL 68.701375 369.467713 \r\nL 68.796221 369.357668 \r\nL 68.904617 369.027533 \r\nL 68.999463 368.917488 \r\nL 69.098825 368.513989 \r\nL 69.134957 368.440625 \r\nL 69.243353 368.055468 \r\nL 69.297551 367.945422 \r\nL 69.40143 367.578605 \r\nL 69.469177 367.46856 \r\nL 69.573056 367.303492 \r\nL 69.627254 367.193447 \r\nL 69.735649 366.588199 \r\nL 69.785331 366.496495 \r\nL 69.893726 365.946269 \r\nL 69.95244 365.836224 \r\nL 70.060836 365.54277 \r\nL 70.078902 365.487748 \r\nL 70.187297 365.120931 \r\nL 70.227946 365.029227 \r\nL 70.327308 364.662409 \r\nL 70.381506 364.552364 \r\nL 70.485385 364.295592 \r\nL 70.535066 364.185547 \r\nL 70.643462 363.873753 \r\nL 70.68411 363.763708 \r\nL 70.77444 363.506936 \r\nL 70.815088 363.415231 \r\nL 70.923484 363.103437 \r\nL 70.959616 362.993392 \r\nL 71.068011 362.846665 \r\nL 71.099627 362.773301 \r\nL 71.18544 362.223076 \r\nL 71.239638 362.149712 \r\nL 71.343517 361.782895 \r\nL 71.406747 361.67285 \r\nL 71.50611 361.342715 \r\nL 71.546758 361.269351 \r\nL 71.650637 360.957557 \r\nL 71.709352 360.847512 \r\nL 71.808714 360.462354 \r\nL 71.849363 360.352309 \r\nL 71.948725 360.113878 \r\nL 71.975824 360.022173 \r\nL 72.08422 359.545311 \r\nL 72.133901 359.435266 \r\nL 72.215198 359.270198 \r\nL 72.319077 359.160153 \r\nL 72.418439 358.774995 \r\nL 72.486186 358.683291 \r\nL 72.590066 358.22477 \r\nL 72.680395 358.114724 \r\nL 72.779758 357.747907 \r\nL 72.838472 357.674544 \r\nL 72.946868 357.307727 \r\nL 73.028164 357.197682 \r\nL 73.127527 356.94091 \r\nL 73.150109 356.867546 \r\nL 73.240439 356.629115 \r\nL 73.317219 356.51907 \r\nL 73.407549 356.243957 \r\nL 73.479812 356.152253 \r\nL 73.588208 355.840458 \r\nL 73.61079 355.767095 \r\nL 73.710153 355.363596 \r\nL 73.786933 355.253551 \r\nL 73.877263 354.978438 \r\nL 73.954043 354.868393 \r\nL 74.057922 354.684985 \r\nL 74.134702 354.59328 \r\nL 74.215999 354.336508 \r\nL 74.283746 354.226463 \r\nL 74.392142 353.859646 \r\nL 74.459889 353.749601 \r\nL 74.568284 353.382784 \r\nL 74.581834 353.272739 \r\nL 74.67668 352.850899 \r\nL 74.776043 352.759195 \r\nL 74.884438 352.282333 \r\nL 74.979284 352.190628 \r\nL 75.07413 351.915516 \r\nL 75.123812 351.823811 \r\nL 75.232207 351.475335 \r\nL 75.263823 351.36529 \r\nL 75.354152 351.090177 \r\nL 75.439965 351.016814 \r\nL 75.539328 350.741701 \r\nL 75.593526 350.631656 \r\nL 75.701921 350.338202 \r\nL 75.814833 350.228157 \r\nL 75.918712 349.953044 \r\nL 75.968394 349.842999 \r\nL 76.076789 349.4395 \r\nL 76.135504 349.347796 \r\nL 76.239383 349.109365 \r\nL 76.280031 348.99932 \r\nL 76.38391 348.559139 \r\nL 76.429075 348.449094 \r\nL 76.528437 348.027254 \r\nL 76.582635 347.917209 \r\nL 76.686514 347.678778 \r\nL 76.754262 347.568733 \r\nL 76.849108 347.220257 \r\nL 76.921371 347.110212 \r\nL 77.020734 346.871781 \r\nL 77.097514 346.780076 \r\nL 77.20591 346.541645 \r\nL 77.242042 346.4316 \r\nL 77.318822 346.138146 \r\nL 77.373019 346.064783 \r\nL 77.481415 345.899715 \r\nL 77.51303 345.78967 \r\nL 77.616909 345.477876 \r\nL 77.671107 345.386171 \r\nL 77.774986 345.221104 \r\nL 77.865316 345.111059 \r\nL 77.973712 344.652537 \r\nL 78.032426 344.542492 \r\nL 78.122755 344.194016 \r\nL 78.217602 344.083971 \r\nL 78.307931 343.84554 \r\nL 78.393744 343.735494 \r\nL 78.50214 343.313655 \r\nL 78.601502 343.20361 \r\nL 78.705382 342.965179 \r\nL 78.786678 342.873474 \r\nL 78.881524 342.451635 \r\nL 78.958304 342.34159 \r\nL 79.053151 342.011454 \r\nL 79.138964 341.901409 \r\nL 79.247359 341.718001 \r\nL 79.288008 341.607955 \r\nL 79.391887 341.149434 \r\nL 79.441568 341.076071 \r\nL 79.545447 340.709254 \r\nL 79.581579 340.63589 \r\nL 79.689975 340.305755 \r\nL 79.717073 340.19571 \r\nL 79.807403 339.865574 \r\nL 79.920315 339.755529 \r\nL 80.024194 339.55378 \r\nL 80.114524 339.443735 \r\nL 80.204853 339.205303 \r\nL 80.263568 339.095258 \r\nL 80.367447 338.746782 \r\nL 80.417128 338.636737 \r\nL 80.525524 338.324942 \r\nL 80.561655 338.214897 \r\nL 80.670051 338.04983 \r\nL 80.701666 337.939784 \r\nL 80.810062 337.701353 \r\nL 80.855227 337.591308 \r\nL 80.963622 337.334536 \r\nL 81.004271 337.242832 \r\nL 81.103633 336.912697 \r\nL 81.180413 336.857674 \r\nL 81.239128 336.619243 \r\nL 81.329457 336.527539 \r\nL 81.41527 336.325789 \r\nL 81.510117 336.215744 \r\nL 81.586897 336.087358 \r\nL 81.663677 335.977313 \r\nL 81.76304 335.757223 \r\nL 81.812721 335.720541 \r\nL 81.921116 335.427087 \r\nL 81.957248 335.317042 \r\nL 82.029512 335.133634 \r\nL 82.137907 335.041929 \r\nL 82.23727 334.766817 \r\nL 82.332116 334.656772 \r\nL 82.431479 334.344977 \r\nL 82.517292 334.234932 \r\nL 82.625687 333.849774 \r\nL 82.688918 333.739729 \r\nL 82.797314 333.464616 \r\nL 82.824413 333.372912 \r\nL 82.932808 333.079458 \r\nL 82.98249 332.969413 \r\nL 83.081852 332.510892 \r\nL 83.154116 332.400846 \r\nL 83.262511 332.107393 \r\nL 83.321226 331.997348 \r\nL 83.429621 331.630531 \r\nL 83.488335 331.520485 \r\nL 83.596731 331.153668 \r\nL 83.619313 331.080305 \r\nL 83.727709 330.823533 \r\nL 83.822555 330.713488 \r\nL 83.926434 330.383352 \r\nL 83.985148 330.273307 \r\nL 84.084511 329.961513 \r\nL 84.129676 329.851468 \r\nL 84.238071 329.539673 \r\nL 84.310335 329.429628 \r\nL 84.418731 329.081152 \r\nL 84.486478 328.989448 \r\nL 84.590357 328.60429 \r\nL 84.635522 328.494244 \r\nL 84.743917 328.054064 \r\nL 84.847796 327.944019 \r\nL 84.951675 327.705588 \r\nL 85.001357 327.595543 \r\nL 85.109752 327.173703 \r\nL 85.172983 327.063658 \r\nL 85.267829 326.843568 \r\nL 85.326543 326.751863 \r\nL 85.434939 326.47675 \r\nL 85.507203 326.366705 \r\nL 85.615598 326.164956 \r\nL 85.678829 326.054911 \r\nL 85.769159 325.889843 \r\nL 85.864005 325.779798 \r\nL 85.9724 325.412981 \r\nL 86.013049 325.302936 \r\nL 86.121444 324.991141 \r\nL 86.189191 324.881096 \r\nL 86.284038 324.459256 \r\nL 86.324686 324.349211 \r\nL 86.405983 324.184144 \r\nL 86.464697 324.074099 \r\nL 86.568576 323.817327 \r\nL 86.591158 323.707281 \r\nL 86.681488 323.395487 \r\nL 86.803433 323.285442 \r\nL 86.907312 323.102033 \r\nL 86.988609 322.991988 \r\nL 87.074422 322.735216 \r\nL 87.124103 322.625171 \r\nL 87.223466 322.350058 \r\nL 87.291213 322.258354 \r\nL 87.399608 321.873196 \r\nL 87.467356 321.781492 \r\nL 87.571235 321.561401 \r\nL 87.620916 321.451356 \r\nL 87.697696 321.359652 \r\nL 87.760927 321.249607 \r\nL 87.855773 321.029517 \r\nL 87.932553 320.937812 \r\nL 88.036432 320.6627 \r\nL 88.10418 320.552654 \r\nL 88.212575 320.204178 \r\nL 88.289355 320.094133 \r\nL 88.397751 319.855702 \r\nL 88.596476 319.745657 \r\nL 88.704872 319.525567 \r\nL 88.772619 319.415521 \r\nL 88.862948 319.17709 \r\nL 88.91263 319.085386 \r\nL 89.011992 318.828614 \r\nL 89.111355 318.73691 \r\nL 89.219751 318.480138 \r\nL 89.301047 318.370093 \r\nL 89.409443 318.021617 \r\nL 89.47719 317.929912 \r\nL 89.572036 317.654799 \r\nL 89.671399 317.544754 \r\nL 89.779794 317.361346 \r\nL 89.856574 317.251301 \r\nL 89.955937 317.01287 \r\nL 90.077882 316.902824 \r\nL 90.177245 316.792779 \r\nL 90.303706 316.682734 \r\nL 90.412102 316.425962 \r\nL 90.475332 316.352599 \r\nL 90.583728 315.875737 \r\nL 90.692123 315.802373 \r\nL 90.78697 315.52726 \r\nL 90.859233 315.417215 \r\nL 90.958596 315.215466 \r\nL 91.10764 315.105421 \r\nL 91.202486 314.958694 \r\nL 91.301848 314.848649 \r\nL 91.410244 314.610218 \r\nL 91.500574 314.500172 \r\nL 91.590903 314.335105 \r\nL 91.758013 314.22506 \r\nL 91.857376 314.02331 \r\nL 91.925123 313.949947 \r\nL 92.029002 313.674834 \r\nL 92.128365 313.564789 \r\nL 92.232244 313.326358 \r\nL 92.299991 313.271335 \r\nL 92.40387 313.051245 \r\nL 92.55743 312.959541 \r\nL 92.661309 312.647746 \r\nL 92.72454 312.556042 \r\nL 92.823903 312.372633 \r\nL 92.918749 312.262588 \r\nL 92.995529 312.005816 \r\nL 93.072309 311.950794 \r\nL 93.176188 311.749044 \r\nL 93.243936 311.638999 \r\nL 93.334265 311.363886 \r\nL 93.397496 311.253841 \r\nL 93.492342 311.107114 \r\nL 93.582672 311.01541 \r\nL 93.686551 310.740297 \r\nL 93.736232 310.648593 \r\nL 93.844628 310.446844 \r\nL 93.948507 310.336799 \r\nL 94.043353 310.116708 \r\nL 94.115616 310.006663 \r\nL 94.214979 309.749891 \r\nL 94.345957 309.658187 \r\nL 94.436287 309.474778 \r\nL 94.50855 309.364733 \r\nL 94.616946 309.107961 \r\nL 94.738891 308.997916 \r\nL 94.838254 308.759485 \r\nL 94.9331 308.64944 \r\nL 95.041495 308.42935 \r\nL 95.100209 308.337645 \r\nL 95.208605 307.989169 \r\nL 95.25377 307.915806 \r\nL 95.362165 307.640693 \r\nL 95.380231 307.56733 \r\nL 95.488627 307.273876 \r\nL 95.506693 307.182172 \r\nL 95.610572 306.888718 \r\nL 95.655737 306.778673 \r\nL 95.746066 306.485219 \r\nL 95.804781 306.411856 \r\nL 95.904143 306.100061 \r\nL 95.998989 306.026698 \r\nL 96.080286 305.751585 \r\nL 96.15255 305.659881 \r\nL 96.260945 305.329745 \r\nL 96.351275 305.2197 \r\nL 96.450637 304.944587 \r\nL 96.500319 304.834542 \r\nL 96.590648 304.632793 \r\nL 96.676461 304.522748 \r\nL 96.780341 304.13759 \r\nL 96.843571 304.027545 \r\nL 96.951967 303.624046 \r\nL 97.019714 303.550682 \r\nL 97.119077 303.202206 \r\nL 97.173274 303.092161 \r\nL 97.28167 302.817048 \r\nL 97.381033 302.707003 \r\nL 97.439747 302.578617 \r\nL 97.575241 302.505254 \r\nL 97.674604 302.156777 \r\nL 97.764934 302.065073 \r\nL 97.873329 301.753279 \r\nL 97.995274 301.643234 \r\nL 98.10367 301.441484 \r\nL 98.193999 301.331439 \r\nL 98.297878 301.166371 \r\nL 98.361109 301.056326 \r\nL 98.469505 300.817895 \r\nL 98.528219 300.70785 \r\nL 98.632098 300.432737 \r\nL 98.722428 300.322692 \r\nL 98.826307 300.157624 \r\nL 98.934702 300.047579 \r\nL 99.015999 299.882511 \r\nL 99.092779 299.772466 \r\nL 99.196658 299.570717 \r\nL 99.246339 299.460672 \r\nL 99.345702 299.350627 \r\nL 99.413449 299.240582 \r\nL 99.503779 299.057173 \r\nL 99.535394 299.020491 \r\nL 99.625724 298.580311 \r\nL 99.716054 298.470266 \r\nL 99.824449 298.34188 \r\nL 99.905746 298.250175 \r\nL 100.009625 297.975063 \r\nL 100.05479 297.883358 \r\nL 100.158669 297.534882 \r\nL 100.212867 297.424837 \r\nL 100.321262 297.223088 \r\nL 100.398042 297.113042 \r\nL 100.501921 296.83793 \r\nL 100.569669 296.764566 \r\nL 100.673548 296.489453 \r\nL 100.709679 296.379408 \r\nL 100.818075 296.049273 \r\nL 100.944537 295.957569 \r\nL 101.052932 295.627433 \r\nL 101.161328 295.535729 \r\nL 101.265207 295.315639 \r\nL 101.378119 295.205594 \r\nL 101.486514 294.893799 \r\nL 101.531679 294.783754 \r\nL 101.640075 294.453619 \r\nL 101.680723 294.380255 \r\nL 101.784602 293.995097 \r\nL 101.888481 293.885052 \r\nL 101.996877 293.664962 \r\nL 102.042042 293.554917 \r\nL 102.150437 293.463212 \r\nL 102.245283 293.353167 \r\nL 102.322063 293.1881 \r\nL 102.407877 293.078054 \r\nL 102.444008 292.876305 \r\nL 102.57047 292.76626 \r\nL 102.678865 292.601192 \r\nL 102.73758 292.491147 \r\nL 102.823393 292.252716 \r\nL 102.949854 292.142671 \r\nL 103.049217 291.849217 \r\nL 103.130514 291.739172 \r\nL 103.220843 291.555764 \r\nL 103.270524 291.445718 \r\nL 103.329239 291.26231 \r\nL 103.527964 291.152265 \r\nL 103.62281 290.84047 \r\nL 103.690557 290.730425 \r\nL 103.798953 290.473653 \r\nL 103.848634 290.363608 \r\nL 103.95703 290.051814 \r\nL 104.015744 289.941768 \r\nL 104.12414 289.648315 \r\nL 104.160271 289.55661 \r\nL 104.268667 289.263157 \r\nL 104.372546 289.153112 \r\nL 104.480942 288.933021 \r\nL 104.535139 288.841317 \r\nL 104.625469 288.676249 \r\nL 104.697733 288.566204 \r\nL 104.783546 288.401137 \r\nL 104.914524 288.291091 \r\nL 105.018403 288.107683 \r\nL 105.113249 287.997638 \r\nL 105.221645 287.795888 \r\nL 105.271326 287.722525 \r\nL 105.379721 287.355708 \r\nL 105.470051 287.264004 \r\nL 105.564897 286.988891 \r\nL 105.709425 286.878846 \r\nL 105.81782 286.658755 \r\nL 105.862985 286.585392 \r\nL 105.948798 286.32862 \r\nL 106.093325 286.218575 \r\nL 106.170106 286.071848 \r\nL 106.246886 285.980144 \r\nL 106.346248 285.760054 \r\nL 106.409479 285.650008 \r\nL 106.517875 285.429918 \r\nL 106.743699 285.319873 \r\nL 106.838545 285.04476 \r\nL 106.937907 284.934715 \r\nL 107.041787 284.714625 \r\nL 107.105017 284.60458 \r\nL 107.208896 284.421171 \r\nL 107.28116 284.311126 \r\nL 107.389556 283.999332 \r\nL 107.461819 283.889286 \r\nL 107.570215 283.614174 \r\nL 107.687643 283.504128 \r\nL 107.787006 283.32072 \r\nL 107.863786 283.210675 \r\nL 107.963149 282.972244 \r\nL 108.048962 282.862199 \r\nL 108.157357 282.715472 \r\nL 108.216072 282.605427 \r\nL 108.310918 282.4587 \r\nL 108.365116 282.348655 \r\nL 108.464478 282.201928 \r\nL 108.563841 282.128564 \r\nL 108.663203 281.853452 \r\nL 108.771599 281.743406 \r\nL 108.879995 281.541657 \r\nL 108.938709 281.431612 \r\nL 109.047104 281.211522 \r\nL 109.092269 281.101477 \r\nL 109.191632 280.936409 \r\nL 109.24583 280.863045 \r\nL 109.331643 280.569592 \r\nL 109.47617 280.459547 \r\nL 109.584566 280.202775 \r\nL 109.638763 280.09273 \r\nL 109.724577 279.89098 \r\nL 109.787807 279.780935 \r\nL 109.88717 279.487481 \r\nL 109.950401 279.395777 \r\nL 110.05428 279.065642 \r\nL 110.090412 278.973937 \r\nL 110.198807 278.772188 \r\nL 110.271071 278.662143 \r\nL 110.379466 278.276985 \r\nL 110.424631 278.185281 \r\nL 110.519477 277.891827 \r\nL 110.61884 277.781782 \r\nL 110.727235 277.598373 \r\nL 110.7724 277.488328 \r\nL 110.880796 277.213215 \r\nL 110.944027 277.121511 \r\nL 111.034356 276.828057 \r\nL 111.111136 276.718012 \r\nL 111.215015 276.332854 \r\nL 111.309862 276.222809 \r\nL 111.413741 275.929356 \r\nL 111.463422 275.837651 \r\nL 111.562785 275.360789 \r\nL 111.675697 275.269085 \r\nL 111.76151 275.030654 \r\nL 111.83829 274.920609 \r\nL 111.924103 274.627155 \r\nL 111.964751 274.535451 \r\nL 112.059598 274.425406 \r\nL 112.122828 274.352042 \r\nL 112.226707 273.911862 \r\nL 112.330586 273.801816 \r\nL 112.438982 273.581726 \r\nL 112.452531 273.508363 \r\nL 112.55641 273.251591 \r\nL 112.66029 273.141546 \r\nL 112.746103 272.994819 \r\nL 112.777718 272.921455 \r\nL 112.881597 272.646343 \r\nL 112.989993 272.536297 \r\nL 113.093872 272.352889 \r\nL 113.179685 272.242844 \r\nL 113.283564 272.114458 \r\nL 113.351311 272.004413 \r\nL 113.441641 271.802663 \r\nL 113.513905 271.692618 \r\nL 113.6223 271.399165 \r\nL 113.726179 271.289119 \r\nL 113.830058 270.922302 \r\nL 113.95652 270.848939 \r\nL 114.024267 270.738894 \r\nL 114.073948 270.66553 \r\nL 114.182344 270.317054 \r\nL 114.295256 270.207009 \r\nL 114.390102 270.00526 \r\nL 114.4443 269.950237 \r\nL 114.552695 269.693465 \r\nL 114.661091 269.58342 \r\nL 114.76497 269.326648 \r\nL 114.850783 269.253285 \r\nL 114.950146 269.124899 \r\nL 114.999827 269.014853 \r\nL 115.090157 268.923149 \r\nL 115.17597 268.831445 \r\nL 115.284365 268.537991 \r\nL 115.383728 268.427946 \r\nL 115.483091 268.171174 \r\nL 115.555354 268.061129 \r\nL 115.659233 267.85938 \r\nL 115.736013 267.767675 \r\nL 115.844409 267.492563 \r\nL 115.939255 267.382517 \r\nL 116.011519 267.199109 \r\nL 116.119914 267.089064 \r\nL 116.214761 266.942337 \r\nL 116.282508 266.868973 \r\nL 116.390903 266.612202 \r\nL 116.445101 266.502156 \r\nL 116.553497 266.35543 \r\nL 116.594145 266.263725 \r\nL 116.693508 266.006953 \r\nL 116.779321 265.896908 \r\nL 116.878683 265.621795 \r\nL 116.982562 265.51175 \r\nL 117.086441 265.254978 \r\nL 117.149672 265.144933 \r\nL 117.230969 264.833139 \r\nL 117.420661 264.723094 \r\nL 117.520024 264.484662 \r\nL 117.678101 264.374617 \r\nL 117.78198 264.191209 \r\nL 117.872309 264.099504 \r\nL 117.980705 263.897755 \r\nL 118.039419 263.824392 \r\nL 118.134265 263.696006 \r\nL 118.192979 263.604301 \r\nL 118.283309 263.292507 \r\nL 118.378155 263.200803 \r\nL 118.459452 263.017394 \r\nL 118.57688 262.907349 \r\nL 118.685276 262.815645 \r\nL 118.712375 262.7056 \r\nL 118.82077 262.50385 \r\nL 118.874968 262.430487 \r\nL 118.906584 262.302101 \r\nL 119.073693 262.192056 \r\nL 119.173056 262.026988 \r\nL 119.227254 261.953624 \r\nL 119.331133 261.733534 \r\nL 119.394364 261.623489 \r\nL 119.498243 261.146627 \r\nL 119.597605 261.036582 \r\nL 119.687935 260.926537 \r\nL 119.832462 260.816492 \r\nL 119.931825 260.541379 \r\nL 120.013121 260.431334 \r\nL 120.117001 260.174562 \r\nL 120.202814 260.064516 \r\nL 120.311209 259.844426 \r\nL 120.356374 259.734381 \r\nL 120.46477 259.49595 \r\nL 120.532517 259.404246 \r\nL 120.631879 259.165815 \r\nL 120.749308 259.055769 \r\nL 120.844154 258.817338 \r\nL 120.979649 258.707293 \r\nL 121.079011 258.340476 \r\nL 121.146758 258.230431 \r\nL 121.237088 258.065363 \r\nL 121.368066 257.955318 \r\nL 121.467429 257.753569 \r\nL 121.562275 257.643524 \r\nL 121.652604 257.441774 \r\nL 121.788099 257.331729 \r\nL 121.896494 257.111639 \r\nL 122.036505 257.001594 \r\nL 122.144901 256.653118 \r\nL 122.262329 256.543072 \r\nL 122.357175 256.451368 \r\nL 122.533318 256.341323 \r\nL 122.637197 256.157914 \r\nL 122.768175 256.047869 \r\nL 122.867538 255.84612 \r\nL 122.948834 255.754416 \r\nL 123.052714 255.479303 \r\nL 123.188208 255.369258 \r\nL 123.274021 255.240872 \r\nL 123.400483 255.130827 \r\nL 123.508878 255.057463 \r\nL 123.612757 254.947418 \r\nL 123.707603 254.819032 \r\nL 123.793416 254.708987 \r\nL 123.86568 254.56226 \r\nL 124.03279 254.452215 \r\nL 124.136669 254.158761 \r\nL 124.1999 254.048716 \r\nL 124.303779 253.846967 \r\nL 124.394109 253.736922 \r\nL 124.475405 253.516831 \r\nL 124.552185 253.461809 \r\nL 124.660581 253.260059 \r\nL 124.732845 253.150014 \r\nL 124.818658 252.984947 \r\nL 124.913504 252.893242 \r\nL 125.021899 252.599789 \r\nL 125.067064 252.489744 \r\nL 125.170943 252.306335 \r\nL 125.25224 252.214631 \r\nL 125.360636 252.031222 \r\nL 125.432899 251.939518 \r\nL 125.541295 251.572701 \r\nL 125.645174 251.462656 \r\nL 125.749053 251.150861 \r\nL 125.834866 251.040816 \r\nL 125.943262 250.784044 \r\nL 126.105855 250.673999 \r\nL 126.191668 250.508931 \r\nL 126.277481 250.398886 \r\nL 126.372327 250.307182 \r\nL 126.480723 250.197137 \r\nL 126.557503 250.032069 \r\nL 126.661382 249.922024 \r\nL 126.756228 249.665252 \r\nL 126.851074 249.555207 \r\nL 126.936888 249.335117 \r\nL 127.018184 249.225071 \r\nL 127.076899 249.096686 \r\nL 127.20336 248.98664 \r\nL 127.307239 248.821573 \r\nL 127.438217 248.711528 \r\nL 127.546613 248.473096 \r\nL 127.623393 248.363051 \r\nL 127.709206 248.234665 \r\nL 127.772437 248.142961 \r\nL 127.817602 248.014575 \r\nL 128.029876 247.90453 \r\nL 128.115689 247.739462 \r\nL 128.228601 247.629417 \r\nL 128.314414 247.48269 \r\nL 128.400228 247.372645 \r\nL 128.508623 247.207577 \r\nL 128.544755 247.097532 \r\nL 128.648634 246.84076 \r\nL 128.802195 246.730715 \r\nL 128.869942 246.565648 \r\nL 129.028019 246.455602 \r\nL 129.136414 246.198831 \r\nL 129.149964 246.107126 \r\nL 129.24481 245.850354 \r\nL 129.326106 245.75865 \r\nL 129.434502 245.483537 \r\nL 129.556447 245.373492 \r\nL 129.660326 245.226765 \r\nL 129.714524 245.11672 \r\nL 129.818403 244.951652 \r\nL 129.88615 244.841607 \r\nL 129.980996 244.67654 \r\nL 130.044227 244.584835 \r\nL 130.121007 244.419768 \r\nL 130.161655 244.346404 \r\nL 130.265535 244.089632 \r\nL 130.346831 243.979587 \r\nL 130.455227 243.851201 \r\nL 130.532007 243.741156 \r\nL 130.626853 243.557747 \r\nL 130.730732 243.447702 \r\nL 130.839128 243.355998 \r\nL 130.947523 243.245953 \r\nL 131.037853 243.099226 \r\nL 131.204963 243.007522 \r\nL 131.290776 242.732409 \r\nL 131.394655 242.640705 \r\nL 131.489501 242.512319 \r\nL 131.561765 242.402274 \r\nL 131.67016 242.182183 \r\nL 131.796622 242.072138 \r\nL 131.905017 241.907071 \r\nL 131.999863 241.815366 \r\nL 132.103742 241.503572 \r\nL 132.153424 241.411867 \r\nL 132.252786 241.100073 \r\nL 132.329567 240.990028 \r\nL 132.428929 240.714915 \r\nL 132.546358 240.60487 \r\nL 132.636687 240.458143 \r\nL 132.717984 240.348098 \r\nL 132.817347 240.072985 \r\nL 132.943808 239.96294 \r\nL 133.052204 239.834554 \r\nL 133.151566 239.724509 \r\nL 133.255445 239.522759 \r\nL 133.318676 239.412714 \r\nL 133.427072 239.174283 \r\nL 133.512885 239.064238 \r\nL 133.571599 238.954193 \r\nL 133.725159 238.844148 \r\nL 133.815489 238.642398 \r\nL 133.937434 238.532353 \r\nL 134.04583 238.275581 \r\nL 134.18584 238.165536 \r\nL 134.280687 237.872083 \r\nL 134.35295 237.762037 \r\nL 134.456829 237.560288 \r\nL 134.515544 237.450243 \r\nL 134.623939 237.285175 \r\nL 134.67362 237.193471 \r\nL 134.7775 236.973381 \r\nL 134.881379 236.863336 \r\nL 134.953642 236.716609 \r\nL 135.143335 236.624904 \r\nL 135.233664 236.478178 \r\nL 135.337543 236.368133 \r\nL 135.441422 236.184724 \r\nL 135.522719 236.074679 \r\nL 135.581433 235.964634 \r\nL 135.734994 235.854589 \r\nL 135.843389 235.579476 \r\nL 135.89307 235.469431 \r\nL 135.987917 235.322704 \r\nL 136.200191 235.212659 \r\nL 136.308587 234.882523 \r\nL 136.353752 234.790819 \r\nL 136.457631 234.534047 \r\nL 136.556993 234.424002 \r\nL 136.642806 234.203912 \r\nL 136.746685 234.093867 \r\nL 136.850565 233.855435 \r\nL 136.990575 233.74539 \r\nL 137.044773 233.617004 \r\nL 137.234465 233.506959 \r\nL 137.320279 233.30521 \r\nL 137.428674 233.195165 \r\nL 137.53707 232.938393 \r\nL 137.672564 232.846688 \r\nL 137.771927 232.681621 \r\nL 137.889355 232.571576 \r\nL 137.997751 232.333145 \r\nL 138.106146 232.223099 \r\nL 138.214542 232.094713 \r\nL 138.286806 231.984668 \r\nL 138.381652 231.874623 \r\nL 138.49908 231.764578 \r\nL 138.602959 231.581169 \r\nL 138.697805 231.471124 \r\nL 138.779102 231.37942 \r\nL 138.905564 231.269375 \r\nL 139.00041 231.104307 \r\nL 139.072673 231.012603 \r\nL 139.15397 230.865876 \r\nL 139.393344 230.755831 \r\nL 139.47464 230.590763 \r\nL 139.623684 230.480718 \r\nL 139.704981 230.260628 \r\nL 139.849508 230.150583 \r\nL 139.953387 229.930493 \r\nL 140.021135 229.820447 \r\nL 140.097915 229.728743 \r\nL 140.21986 229.618698 \r\nL 140.274058 229.43529 \r\nL 140.481816 229.343585 \r\nL 140.590211 229.178518 \r\nL 140.734739 229.068472 \r\nL 140.779903 228.958427 \r\nL 140.897332 228.848382 \r\nL 141.005728 228.628292 \r\nL 141.199936 228.518247 \r\nL 141.308332 228.389861 \r\nL 141.389628 228.279816 \r\nL 141.479958 227.94968 \r\nL 141.561255 227.839635 \r\nL 141.642551 227.711249 \r\nL 141.714815 227.601204 \r\nL 141.814178 227.472818 \r\nL 141.899991 227.362773 \r\nL 141.999353 227.197705 \r\nL 142.076134 227.08766 \r\nL 142.143881 226.959274 \r\nL 142.279375 226.849229 \r\nL 142.369705 226.794206 \r\nL 142.437452 226.684161 \r\nL 142.532298 226.519094 \r\nL 142.690375 226.409049 \r\nL 142.789738 226.207299 \r\nL 142.866518 226.097254 \r\nL 142.965881 225.895505 \r\nL 143.092342 225.8038 \r\nL 143.191705 225.638733 \r\nL 143.318166 225.565369 \r\nL 143.37688 225.418642 \r\nL 143.580122 225.308597 \r\nL 143.684001 225.16187 \r\nL 143.769814 225.051825 \r\nL 143.851111 224.868417 \r\nL 143.936924 224.758372 \r\nL 144.027254 224.703349 \r\nL 144.104034 224.593304 \r\nL 144.153715 224.446577 \r\nL 144.338891 224.336532 \r\nL 144.438254 224.171464 \r\nL 144.537616 224.061419 \r\nL 144.636979 223.933033 \r\nL 144.844737 223.822988 \r\nL 144.953132 223.63958 \r\nL 145.075077 223.529534 \r\nL 145.183473 223.346126 \r\nL 145.260253 223.236081 \r\nL 145.332517 223.089354 \r\nL 145.526726 222.979309 \r\nL 145.630605 222.814241 \r\nL 145.729967 222.704196 \r\nL 145.729967 222.685855 \r\nL 145.951275 222.57581 \r\nL 146.009989 222.484106 \r\nL 146.140967 222.374061 \r\nL 146.24033 222.172311 \r\nL 146.362275 222.062266 \r\nL 146.466154 221.878857 \r\nL 146.588099 221.768812 \r\nL 146.696494 221.585404 \r\nL 146.859088 221.475359 \r\nL 146.949417 221.328632 \r\nL 147.134593 221.218587 \r\nL 147.220406 220.980156 \r\nL 147.382999 220.888451 \r\nL 147.468813 220.613339 \r\nL 147.572692 220.521634 \r\nL 147.604307 220.393248 \r\nL 147.757867 220.283203 \r\nL 147.843681 220.118135 \r\nL 147.983691 220.00809 \r\nL 148.092087 219.769659 \r\nL 148.1779 219.659614 \r\nL 148.286296 219.494546 \r\nL 148.394691 219.384501 \r\nL 148.503087 219.237774 \r\nL 148.625032 219.127729 \r\nL 148.724394 218.92598 \r\nL 148.805691 218.815935 \r\nL 148.891504 218.724231 \r\nL 148.9999 218.614185 \r\nL 149.090229 218.50414 \r\nL 149.221207 218.394095 \r\nL 149.316054 218.28405 \r\nL 149.39735 218.174005 \r\nL 149.492196 217.990596 \r\nL 149.663823 217.880551 \r\nL 149.772218 217.678802 \r\nL 149.889647 217.587098 \r\nL 149.998042 217.348666 \r\nL 150.223866 217.256962 \r\nL 150.300647 217.018531 \r\nL 150.458723 216.908486 \r\nL 150.549053 216.743418 \r\nL 150.743262 216.633373 \r\nL 150.851657 216.504987 \r\nL 150.991668 216.394942 \r\nL 151.050382 216.174852 \r\nL 151.199426 216.064807 \r\nL 151.289756 215.881398 \r\nL 151.420734 215.771353 \r\nL 151.520097 215.69799 \r\nL 151.646558 215.587944 \r\nL 151.750437 215.349513 \r\nL 151.813668 215.239468 \r\nL 151.818184 215.202786 \r\nL 152.00336 215.092741 \r\nL 152.098206 214.890992 \r\nL 152.269832 214.780947 \r\nL 152.373712 214.560857 \r\nL 152.500173 214.450811 \r\nL 152.604052 214.285744 \r\nL 152.653733 214.175699 \r\nL 152.762129 213.955608 \r\nL 152.879557 213.845563 \r\nL 152.983437 213.662155 \r\nL 153.087316 213.55211 \r\nL 153.182162 213.460405 \r\nL 153.263458 213.35036 \r\nL 153.367337 213.148611 \r\nL 153.448634 213.038566 \r\nL 153.552513 212.763453 \r\nL 153.651876 212.653408 \r\nL 153.755755 212.469999 \r\nL 153.859634 212.359954 \r\nL 153.949964 212.194886 \r\nL 154.053843 212.084841 \r\nL 154.157722 211.864751 \r\nL 154.229985 211.754706 \r\nL 154.329348 211.62632 \r\nL 154.419678 211.516275 \r\nL 154.51904 211.222821 \r\nL 154.668084 211.167798 \r\nL 154.771963 210.892686 \r\nL 154.862293 210.782641 \r\nL 154.966172 210.635914 \r\nL 155.079084 210.525869 \r\nL 155.17393 210.34246 \r\nL 155.282326 210.232415 \r\nL 155.377172 210.049006 \r\nL 155.503633 209.938961 \r\nL 155.612029 209.847257 \r\nL 155.724941 209.737212 \r\nL 155.792688 209.627167 \r\nL 155.937215 209.517122 \r\nL 156.036578 209.370395 \r\nL 156.108842 209.26035 \r\nL 156.190138 209.113623 \r\nL 156.379831 209.003578 \r\nL 156.48371 208.893533 \r\nL 156.578556 208.801828 \r\nL 156.673402 208.545056 \r\nL 156.826962 208.435011 \r\nL 156.912775 208.343307 \r\nL 157.030204 208.251603 \r\nL 157.1386 208.049853 \r\nL 157.27861 207.939808 \r\nL 157.373457 207.848104 \r\nL 157.5225 207.738059 \r\nL 157.62638 207.664695 \r\nL 157.725742 207.55465 \r\nL 157.834138 207.33456 \r\nL 157.915434 207.224515 \r\nL 157.951566 207.132811 \r\nL 158.091577 207.022765 \r\nL 158.199973 206.674289 \r\nL 158.330951 206.564244 \r\nL 158.439346 206.307472 \r\nL 158.552258 206.197427 \r\nL 158.633555 206.105723 \r\nL 158.750983 205.995678 \r\nL 158.854863 205.885632 \r\nL 158.927126 205.793928 \r\nL 159.026489 205.665542 \r\nL 159.121335 205.555497 \r\nL 159.184566 205.427111 \r\nL 159.292961 205.353748 \r\nL 159.39684 205.078635 \r\nL 159.523302 204.986931 \r\nL 159.631697 204.858545 \r\nL 159.712994 204.748499 \r\nL 159.816873 204.510068 \r\nL 159.89817 204.418364 \r\nL 160.002049 204.216615 \r\nL 160.169159 204.10657 \r\nL 160.277554 203.959843 \r\nL 160.3724 203.849798 \r\nL 160.471763 203.648048 \r\nL 160.61629 203.538003 \r\nL 160.711136 203.336254 \r\nL 160.824048 203.226209 \r\nL 160.891796 203.061141 \r\nL 161.045356 202.951096 \r\nL 161.153752 202.841051 \r\nL 161.257631 202.731005 \r\nL 161.366026 202.639301 \r\nL 161.478938 202.529256 \r\nL 161.578301 202.382529 \r\nL 161.637015 202.290825 \r\nL 161.731861 202.089076 \r\nL 161.858323 201.97903 \r\nL 161.953169 201.795622 \r\nL 162.048015 201.703918 \r\nL 162.129312 201.557191 \r\nL 162.278355 201.447146 \r\nL 162.364169 201.355441 \r\nL 162.440949 201.245396 \r\nL 162.540311 201.11701 \r\nL 162.653223 201.006965 \r\nL 162.761619 200.823557 \r\nL 162.851949 200.731852 \r\nL 162.951311 200.566785 \r\nL 163.046157 200.456739 \r\nL 163.150036 200.291672 \r\nL 163.308113 200.181627 \r\nL 163.407476 200.0349 \r\nL 163.552003 199.924855 \r\nL 163.646849 199.778128 \r\nL 163.859124 199.668083 \r\nL 163.949454 199.558038 \r\nL 164.062366 199.447992 \r\nL 164.170761 199.246243 \r\nL 164.265607 199.136198 \r\nL 164.374003 198.97113 \r\nL 164.568212 198.861085 \r\nL 164.676607 198.696017 \r\nL 164.735321 198.585972 \r\nL 164.843717 198.274178 \r\nL 164.934047 198.182474 \r\nL 165.024376 197.962383 \r\nL 165.105673 197.852338 \r\nL 165.205036 197.705611 \r\nL 165.286332 197.595566 \r\nL 165.390211 197.448839 \r\nL 165.552805 197.357135 \r\nL 165.656684 197.137045 \r\nL 165.841859 197.027 \r\nL 165.950255 196.880273 \r\nL 166.117365 196.770228 \r\nL 166.198661 196.660183 \r\nL 166.415453 196.550137 \r\nL 166.505782 196.403411 \r\nL 166.623211 196.311706 \r\nL 166.686441 196.201661 \r\nL 166.808386 196.091616 \r\nL 166.912266 195.889867 \r\nL 167.025178 195.779822 \r\nL 167.115507 195.596413 \r\nL 167.20132 195.486368 \r\nL 167.287133 195.339641 \r\nL 167.38198 195.247937 \r\nL 167.400046 195.192914 \r\nL 167.567155 195.082869 \r\nL 167.666518 194.936142 \r\nL 167.806529 194.826097 \r\nL 167.910408 194.624348 \r\nL 168.027836 194.514303 \r\nL 168.122683 194.349235 \r\nL 168.19043 194.23919 \r\nL 168.294309 194.0191 \r\nL 168.497551 193.909054 \r\nL 168.58788 193.799009 \r\nL 168.700792 193.688964 \r\nL 168.782089 193.560578 \r\nL 168.944682 193.450533 \r\nL 169.053078 193.285465 \r\nL 169.134374 193.193761 \r\nL 169.220188 193.010353 \r\nL 169.315034 192.900307 \r\nL 169.414396 192.753581 \r\nL 169.527308 192.661876 \r\nL 169.631187 192.570172 \r\nL 169.680869 192.478468 \r\nL 169.775715 192.368423 \r\nL 169.906693 192.258378 \r\nL 170.015088 192.166673 \r\nL 170.128 192.056628 \r\nL 170.227363 191.983265 \r\nL 170.304143 191.87322 \r\nL 170.389956 191.744834 \r\nL 170.475769 191.634788 \r\nL 170.570616 191.488062 \r\nL 170.719659 191.396357 \r\nL 170.819022 191.139585 \r\nL 170.954516 191.02954 \r\nL 171.058396 190.827791 \r\nL 171.234538 190.717746 \r\nL 171.338417 190.534337 \r\nL 171.487461 190.424292 \r\nL 171.582307 190.314247 \r\nL 171.699736 190.204202 \r\nL 171.799099 189.94743 \r\nL 171.866846 189.837385 \r\nL 171.893945 189.74568 \r\nL 172.020406 189.635635 \r\nL 172.128802 189.397204 \r\nL 172.313977 189.287159 \r\nL 172.41334 189.177114 \r\nL 172.521736 189.067069 \r\nL 172.630131 188.938683 \r\nL 172.765626 188.828638 \r\nL 172.869505 188.773615 \r\nL 172.946285 188.66357 \r\nL 173.045647 188.480162 \r\nL 173.266955 188.370116 \r\nL 173.375351 188.24173 \r\nL 173.443098 188.131685 \r\nL 173.528911 187.984958 \r\nL 173.686988 187.874913 \r\nL 173.777317 187.636482 \r\nL 173.921845 187.526437 \r\nL 173.998625 187.361369 \r\nL 174.174768 187.251324 \r\nL 174.219933 187.141279 \r\nL 174.355427 187.031234 \r\nL 174.427691 186.774462 \r\nL 174.53157 186.664417 \r\nL 174.576735 186.572713 \r\nL 174.721262 186.462668 \r\nL 174.825141 186.260918 \r\nL 174.892888 186.150873 \r\nL 174.996767 186.022487 \r\nL 175.064515 185.912442 \r\nL 175.109679 185.820738 \r\nL 175.26324 185.729033 \r\nL 175.371635 185.582307 \r\nL 175.516163 185.472261 \r\nL 175.620042 185.215489 \r\nL 175.760053 185.105444 \r\nL 175.863932 184.940377 \r\nL 176.003943 184.830331 \r\nL 176.098789 184.665264 \r\nL 176.22525 184.555219 \r\nL 176.320097 184.408492 \r\nL 176.460107 184.298447 \r\nL 176.550437 184.15172 \r\nL 176.627217 184.096697 \r\nL 176.681415 183.968311 \r\nL 176.920789 183.894948 \r\nL 177.029184 183.656517 \r\nL 177.119514 183.564813 \r\nL 177.21436 183.436427 \r\nL 177.273074 183.326381 \r\nL 177.38147 183.197995 \r\nL 177.53503 183.106291 \r\nL 177.643426 182.904542 \r\nL 177.733755 182.794497 \r\nL 177.828601 182.64777 \r\nL 177.900865 182.537725 \r\nL 177.995711 182.390998 \r\nL 178.162821 182.280953 \r\nL 178.271217 182.134226 \r\nL 178.35703 182.024181 \r\nL 178.456392 181.914136 \r\nL 178.560271 181.804091 \r\nL 178.623502 181.657364 \r\nL 178.808678 181.565659 \r\nL 178.876425 181.437273 \r\nL 179.020952 181.327228 \r\nL 179.120315 181.235524 \r\nL 179.228711 181.125479 \r\nL 179.31904 180.997093 \r\nL 179.490667 180.887048 \r\nL 179.567447 180.795344 \r\nL 179.666809 180.685298 \r\nL 179.766172 180.575253 \r\nL 179.951348 180.465208 \r\nL 180.059743 180.318481 \r\nL 180.109425 180.208436 \r\nL 180.204271 180.061709 \r\nL 180.285567 179.951664 \r\nL 180.353315 179.85996 \r\nL 180.46171 179.749915 \r\nL 180.556556 179.584847 \r\nL 180.723666 179.474802 \r\nL 180.777864 179.364757 \r\nL 180.981105 179.254712 \r\nL 181.071435 179.126326 \r\nL 181.179831 179.016281 \r\nL 181.279193 178.77785 \r\nL 181.43727 178.667804 \r\nL 181.523083 178.5761 \r\nL 181.730841 178.466055 \r\nL 181.794072 178.374351 \r\nL 182.024413 178.264306 \r\nL 182.132808 178.117579 \r\nL 182.205072 178.007534 \r\nL 182.304435 177.842466 \r\nL 182.435412 177.732421 \r\nL 182.512193 177.622376 \r\nL 182.647687 177.512331 \r\nL 182.7335 177.383945 \r\nL 182.91416 177.273899 \r\nL 182.986423 177.145513 \r\nL 183.171599 177.035468 \r\nL 183.270962 176.85206 \r\nL 183.347742 176.760356 \r\nL 183.410973 176.576947 \r\nL 183.514852 176.466902 \r\nL 183.614214 176.228471 \r\nL 183.772291 176.136766 \r\nL 183.831005 176.026721 \r\nL 183.993599 175.935017 \r\nL 184.097478 175.733268 \r\nL 184.214906 175.641563 \r\nL 184.296203 175.513177 \r\nL 184.476862 175.403132 \r\nL 184.553642 175.329769 \r\nL 184.765917 175.219724 \r\nL 184.869796 174.999634 \r\nL 184.973675 174.889588 \r\nL 185.073038 174.724521 \r\nL 185.199499 174.614476 \r\nL 185.303378 174.50443 \r\nL 185.461455 174.394385 \r\nL 185.511136 174.302681 \r\nL 185.646631 174.229318 \r\nL 185.723411 174.119272 \r\nL 185.872455 174.009227 \r\nL 185.976334 173.862501 \r\nL 186.138927 173.752455 \r\nL 186.247323 173.624069 \r\nL 186.301521 173.532365 \r\nL 186.409916 173.440661 \r\nL 186.55896 173.330616 \r\nL 186.64929 173.275593 \r\nL 186.784784 173.165548 \r\nL 186.875114 173.055503 \r\nL 187.037707 172.945458 \r\nL 187.146103 172.817072 \r\nL 187.272564 172.707027 \r\nL 187.349344 172.615322 \r\nL 187.525487 172.505277 \r\nL 187.620333 172.395232 \r\nL 187.850674 172.285187 \r\nL 187.900355 172.211824 \r\nL 188.103597 172.101778 \r\nL 188.198443 172.028415 \r\nL 188.297805 171.936711 \r\nL 188.401685 171.789984 \r\nL 188.487498 171.679939 \r\nL 188.58686 171.514871 \r\nL 188.690739 171.404826 \r\nL 188.794618 171.368144 \r\nL 188.889465 171.258099 \r\nL 188.99786 170.982986 \r\nL 189.115289 170.872941 \r\nL 189.223684 170.762896 \r\nL 189.341113 170.689533 \r\nL 189.449508 170.451102 \r\nL 189.625651 170.341056 \r\nL 189.734047 170.120966 \r\nL 189.851475 170.010921 \r\nL 189.946321 169.827513 \r\nL 190.145046 169.717467 \r\nL 190.253442 169.607422 \r\nL 190.30764 169.515718 \r\nL 190.416035 169.222264 \r\nL 190.533464 169.112219 \r\nL 190.637343 168.983833 \r\nL 190.768321 168.873788 \r\nL 190.876716 168.745402 \r\nL 191.129639 168.653698 \r\nL 191.201903 168.48863 \r\nL 191.287716 168.396926 \r\nL 191.387079 168.213517 \r\nL 191.585804 168.103472 \r\nL 191.689683 167.993427 \r\nL 191.793562 167.883382 \r\nL 191.897441 167.773337 \r\nL 192.01487 167.681633 \r\nL 192.123265 167.553247 \r\nL 192.326507 167.443201 \r\nL 192.434903 167.314815 \r\nL 192.570397 167.223111 \r\nL 192.65621 167.076384 \r\nL 192.782672 166.966339 \r\nL 192.891067 166.819612 \r\nL 193.035595 166.709567 \r\nL 193.134957 166.5445 \r\nL 193.265935 166.434454 \r\nL 193.369814 166.34275 \r\nL 193.505309 166.232705 \r\nL 193.595638 166.12266 \r\nL 193.695001 166.030956 \r\nL 193.79888 165.792525 \r\nL 193.916309 165.70082 \r\nL 194.020188 165.535753 \r\nL 194.164715 165.425707 \r\nL 194.268594 165.315662 \r\nL 194.358924 165.205617 \r\nL 194.462803 165.04055 \r\nL 194.580231 164.930504 \r\nL 194.643462 164.820459 \r\nL 194.918967 164.710414 \r\nL 195.027363 164.61871 \r\nL 195.131242 164.508665 \r\nL 195.198989 164.435301 \r\nL 195.311901 164.325256 \r\nL 195.411264 164.160189 \r\nL 195.515143 164.086825 \r\nL 195.609989 163.940098 \r\nL 195.772582 163.830053 \r\nL 195.867429 163.683326 \r\nL 196.052604 163.573281 \r\nL 196.161 163.353191 \r\nL 196.228747 163.243146 \r\nL 196.323593 163.133101 \r\nL 196.427472 163.023056 \r\nL 196.526835 162.968033 \r\nL 196.644263 162.857988 \r\nL 196.702978 162.747943 \r\nL 196.906219 162.656238 \r\nL 197.001065 162.546193 \r\nL 197.159142 162.454489 \r\nL 197.267538 162.25274 \r\nL 197.416582 162.142695 \r\nL 197.506911 161.977627 \r\nL 197.655955 161.867582 \r\nL 197.737252 161.775877 \r\nL 197.863713 161.665832 \r\nL 197.958559 161.537446 \r\nL 198.09857 161.427401 \r\nL 198.202449 161.317356 \r\nL 198.310845 161.207311 \r\nL 198.419241 161.078925 \r\nL 198.52312 160.96888 \r\nL 198.626999 160.877176 \r\nL 198.739911 160.76713 \r\nL 198.807658 160.693767 \r\nL 198.979284 160.583722 \r\nL 199.078647 160.363632 \r\nL 199.223174 160.271927 \r\nL 199.281889 160.198564 \r\nL 199.372218 160.088519 \r\nL 199.417383 160.033496 \r\nL 199.521262 159.923451 \r\nL 199.607075 159.758383 \r\nL 199.724504 159.648338 \r\nL 199.810317 159.519952 \r\nL 199.945811 159.409907 \r\nL 200.027108 159.281521 \r\nL 200.338745 159.171476 \r\nL 200.411009 159.116454 \r\nL 200.573602 159.006408 \r\nL 200.681998 158.914704 \r\nL 200.754262 158.804659 \r\nL 200.858141 158.639591 \r\nL 201.106547 158.529546 \r\nL 201.178811 158.364479 \r\nL 201.345921 158.272774 \r\nL 201.454316 158.126047 \r\nL 201.594327 158.016002 \r\nL 201.675624 157.814253 \r\nL 201.784019 157.704208 \r\nL 201.887898 157.630844 \r\nL 202.122755 157.520799 \r\nL 202.231151 157.337391 \r\nL 202.393744 157.227346 \r\nL 202.493107 157.025596 \r\nL 202.601502 156.915551 \r\nL 202.709898 156.750483 \r\nL 202.858942 156.640438 \r\nL 202.962821 156.530393 \r\nL 203.080249 156.420348 \r\nL 203.170579 156.291962 \r\nL 203.355755 156.181917 \r\nL 203.455117 156.071872 \r\nL 203.518348 155.980167 \r\nL 203.608678 155.833441 \r\nL 203.72159 155.723395 \r\nL 203.825469 155.595009 \r\nL 204.04226 155.484964 \r\nL 204.114524 155.374919 \r\nL 204.245502 155.264874 \r\nL 204.353897 155.17317 \r\nL 204.570688 155.081466 \r\nL 204.665535 154.97142 \r\nL 204.828128 154.861375 \r\nL 204.932007 154.769671 \r\nL 205.022337 154.677967 \r\nL 205.099117 154.549581 \r\nL 205.442369 154.439536 \r\nL 205.550765 154.201105 \r\nL 205.830787 154.091059 \r\nL 205.930149 153.907651 \r\nL 206.024995 153.797606 \r\nL 206.110809 153.687561 \r\nL 206.232754 153.595856 \r\nL 206.323083 153.44913 \r\nL 206.544391 153.339084 \r\nL 206.652786 153.229039 \r\nL 206.761182 153.137335 \r\nL 206.860545 153.02729 \r\nL 206.96894 152.917245 \r\nL 207.04572 152.82554 \r\nL 207.21283 152.715495 \r\nL 207.321226 152.587109 \r\nL 207.556083 152.477064 \r\nL 207.646412 152.348678 \r\nL 207.86772 152.256974 \r\nL 207.949017 152.146929 \r\nL 208.066445 152.036884 \r\nL 208.11161 151.96352 \r\nL 208.229038 151.853475 \r\nL 208.310335 151.780112 \r\nL 208.563258 151.670067 \r\nL 208.671654 151.468317 \r\nL 208.802632 151.358272 \r\nL 208.883928 151.284909 \r\nL 209.091686 151.174864 \r\nL 209.172983 151.064818 \r\nL 209.358159 150.954773 \r\nL 209.457521 150.808046 \r\nL 209.647214 150.698001 \r\nL 209.746576 150.551275 \r\nL 209.931752 150.441229 \r\nL 210.040148 150.367866 \r\nL 210.121444 150.257821 \r\nL 210.22984 150.166117 \r\nL 210.333719 150.056071 \r\nL 210.437598 149.872663 \r\nL 210.609224 149.762618 \r\nL 210.708587 149.560868 \r\nL 210.839565 149.450823 \r\nL 210.916345 149.322437 \r\nL 211.083455 149.212392 \r\nL 211.187334 149.102347 \r\nL 211.340894 148.992302 \r\nL 211.440257 148.845575 \r\nL 211.611883 148.73553 \r\nL 211.715762 148.625485 \r\nL 211.986751 148.533781 \r\nL 212.086114 148.368713 \r\nL 212.266773 148.258668 \r\nL 212.357103 148.056918 \r\nL 212.573894 147.946873 \r\nL 212.664223 147.87351 \r\nL 212.935212 147.763465 \r\nL 213.002959 147.67176 \r\nL 213.129421 147.561715 \r\nL 213.210718 147.359966 \r\nL 213.314597 147.249921 \r\nL 213.40041 147.139876 \r\nL 213.689465 147.02983 \r\nL 213.793344 146.754718 \r\nL 213.910772 146.644673 \r\nL 214.010135 146.516287 \r\nL 214.344354 146.406241 \r\nL 214.45275 146.332878 \r\nL 214.574695 146.222833 \r\nL 214.665025 146.112788 \r\nL 214.814068 146.021083 \r\nL 214.922464 145.94772 \r\nL 214.985695 145.837675 \r\nL 215.089574 145.654266 \r\nL 215.188936 145.544221 \r\nL 215.297332 145.379154 \r\nL 215.545738 145.269108 \r\nL 215.640585 145.140722 \r\nL 215.776079 145.030677 \r\nL 215.875442 144.810587 \r\nL 216.019969 144.700542 \r\nL 216.128365 144.590497 \r\nL 216.272892 144.480452 \r\nL 216.358705 144.407088 \r\nL 216.543881 144.297043 \r\nL 216.620661 144.168657 \r\nL 216.73809 144.076953 \r\nL 216.81487 143.948567 \r\nL 216.991013 143.838522 \r\nL 217.054243 143.728477 \r\nL 217.275551 143.618432 \r\nL 217.352331 143.526727 \r\nL 217.501375 143.435023 \r\nL 217.605254 143.251614 \r\nL 217.686551 143.141569 \r\nL 217.79043 143.031524 \r\nL 217.998188 142.921479 \r\nL 218.088518 142.774752 \r\nL 218.233045 142.664707 \r\nL 218.323375 142.536321 \r\nL 218.499517 142.426276 \r\nL 218.603396 142.261208 \r\nL 218.770506 142.151163 \r\nL 218.874385 142.022777 \r\nL 219.014396 141.931073 \r\nL 219.118275 141.802687 \r\nL 219.217638 141.692642 \r\nL 219.321517 141.582597 \r\nL 219.457011 141.472552 \r\nL 219.565407 141.362506 \r\nL 219.682836 141.252461 \r\nL 219.759616 141.124075 \r\nL 219.913176 141.01403 \r\nL 219.967374 140.940667 \r\nL 220.134484 140.830622 \r\nL 220.220297 140.720577 \r\nL 220.568066 140.610531 \r\nL 220.658396 140.482145 \r\nL 220.753242 140.3721 \r\nL 220.861637 140.225373 \r\nL 221.060362 140.115328 \r\nL 221.164241 139.986942 \r\nL 221.286186 139.876897 \r\nL 221.367483 139.71183 \r\nL 221.588791 139.601784 \r\nL 221.688153 139.436717 \r\nL 221.755901 139.363353 \r\nL 221.864296 139.124922 \r\nL 221.93656 139.014877 \r\nL 222.026889 138.923173 \r\nL 222.261746 138.813128 \r\nL 222.370142 138.666401 \r\nL 222.442406 138.556356 \r\nL 222.546285 138.464651 \r\nL 222.704362 138.354606 \r\nL 222.749526 138.22622 \r\nL 222.925669 138.116175 \r\nL 223.029548 138.00613 \r\nL 223.119878 137.896085 \r\nL 223.183109 137.78604 \r\nL 223.521845 137.694336 \r\nL 223.625724 137.602631 \r\nL 223.725087 137.492586 \r\nL 223.828966 137.382541 \r\nL 223.982526 137.272496 \r\nL 224.068339 137.180792 \r\nL 224.289647 137.070746 \r\nL 224.398042 136.997383 \r\nL 224.673548 136.887338 \r\nL 224.777427 136.740611 \r\nL 224.890339 136.630566 \r\nL 224.962602 136.447157 \r\nL 225.238108 136.355453 \r\nL 225.346503 136.190385 \r\nL 225.486514 136.08034 \r\nL 225.572327 135.951954 \r\nL 225.771053 135.841909 \r\nL 225.874932 135.585137 \r\nL 226.06914 135.475092 \r\nL 226.141404 135.310024 \r\nL 226.367228 135.199979 \r\nL 226.394327 135.163298 \r\nL 226.602085 135.053252 \r\nL 226.696931 134.924867 \r\nL 226.904689 134.869844 \r\nL 227.008569 134.704776 \r\nL 227.085349 134.613072 \r\nL 227.189228 134.448004 \r\nL 227.333755 134.337959 \r\nL 227.442151 134.172891 \r\nL 227.658942 134.062846 \r\nL 227.753788 133.989483 \r\nL 227.875733 133.879438 \r\nL 227.961546 133.787734 \r\nL 228.101557 133.696029 \r\nL 228.205436 133.549302 \r\nL 228.358997 133.439257 \r\nL 228.458359 133.237508 \r\nL 228.684183 133.127463 \r\nL 228.733865 133.054099 \r\nL 228.928073 132.944054 \r\nL 229.036469 132.834009 \r\nL 229.190029 132.723964 \r\nL 229.298425 132.63226 \r\nL 229.402304 132.540555 \r\nL 229.49715 132.338806 \r\nL 229.700392 132.228761 \r\nL 229.808787 132.082034 \r\nL 229.876534 131.971989 \r\nL 229.912666 131.935307 \r\nL 230.278501 131.843603 \r\nL 230.38238 131.678535 \r\nL 230.54949 131.56849 \r\nL 230.657886 131.421763 \r\nL 230.811446 131.311718 \r\nL 230.892743 131.220014 \r\nL 231.159215 131.109969 \r\nL 231.245028 131.018265 \r\nL 231.457303 130.908219 \r\nL 231.565698 130.798174 \r\nL 231.818621 130.688129 \r\nL 231.917984 130.596425 \r\nL 232.071544 130.48638 \r\nL 232.17994 130.321312 \r\nL 232.292852 130.211267 \r\nL 232.387698 130.101222 \r\nL 232.57739 129.991177 \r\nL 232.672236 129.826109 \r\nL 232.807731 129.716064 \r\nL 232.875478 129.62436 \r\nL 233.137434 129.514314 \r\nL 233.214214 129.459292 \r\nL 233.349709 129.349247 \r\nL 233.363258 129.294224 \r\nL 233.55295 129.20252 \r\nL 233.620698 129.092475 \r\nL 233.869104 128.98243 \r\nL 233.896203 128.890725 \r\nL 234.144609 128.78068 \r\nL 234.234939 128.633953 \r\nL 234.474313 128.523908 \r\nL 234.474313 128.505567 \r\nL 234.871763 128.395522 \r\nL 234.930477 128.322159 \r\nL 235.219532 128.212114 \r\nL 235.323411 128.065387 \r\nL 235.400191 127.973683 \r\nL 235.508587 127.826956 \r\nL 235.689246 127.716911 \r\nL 235.76151 127.680229 \r\nL 235.901521 127.570184 \r\nL 236.009916 127.49682 \r\nL 236.17251 127.386775 \r\nL 236.271872 127.258389 \r\nL 236.597059 127.166685 \r\nL 236.700938 127.038299 \r\nL 236.863531 126.946595 \r\nL 236.944828 126.83655 \r\nL 237.125487 126.726505 \r\nL 237.215817 126.671482 \r\nL 237.328729 126.579778 \r\nL 237.437124 126.41471 \r\nL 237.559069 126.304665 \r\nL 237.644883 126.212961 \r\nL 237.802959 126.102916 \r\nL 237.875223 126.066234 \r\nL 238.236542 125.956189 \r\nL 238.344937 125.809462 \r\nL 238.399135 125.699417 \r\nL 238.503014 125.589372 \r\nL 238.751421 125.479326 \r\nL 238.796585 125.424304 \r\nL 238.968212 125.3326 \r\nL 239.063058 125.222555 \r\nL 239.297915 125.112509 \r\nL 239.401794 125.057487 \r\nL 239.568904 124.947442 \r\nL 239.641167 124.892419 \r\nL 239.871508 124.782374 \r\nL 239.979903 124.69067 \r\nL 240.083783 124.580625 \r\nL 240.187662 124.470579 \r\nL 240.39542 124.360534 \r\nL 240.503815 124.213808 \r\nL 240.648343 124.103762 \r\nL 240.71609 124.012058 \r\nL 240.878683 123.902013 \r\nL 240.950947 123.755286 \r\nL 241.208386 123.645241 \r\nL 241.212903 123.608559 \r\nL 241.452276 123.498514 \r\nL 241.556156 123.388469 \r\nL 241.78198 123.278424 \r\nL 241.795529 123.223401 \r\nL 242.080067 123.113356 \r\nL 242.183946 123.039993 \r\nL 242.382672 122.929948 \r\nL 242.463968 122.856584 \r\nL 242.572364 122.746539 \r\nL 242.66721 122.654835 \r\nL 242.929166 122.563131 \r\nL 243.024012 122.361381 \r\nL 243.186605 122.251336 \r\nL 243.285968 122.159632 \r\nL 243.633737 122.049587 \r\nL 243.7331 121.976223 \r\nL 243.96344 121.866178 \r\nL 244.049253 121.811156 \r\nL 244.193781 121.70111 \r\nL 244.28411 121.646088 \r\nL 244.419605 121.536043 \r\nL 244.500901 121.425998 \r\nL 244.70866 121.315953 \r\nL 244.776407 121.242589 \r\nL 244.966099 121.132544 \r\nL 245.069978 121.004158 \r\nL 245.295802 120.894113 \r\nL 245.372582 120.857431 \r\nL 245.59389 120.747386 \r\nL 245.702286 120.710704 \r\nL 245.946176 120.637341 \r\nL 246.054571 120.453932 \r\nL 246.15845 120.343887 \r\nL 246.253296 120.252183 \r\nL 246.474604 120.142138 \r\nL 246.573966 119.958729 \r\nL 246.826889 119.848684 \r\nL 246.935285 119.720298 \r\nL 247.05723 119.610253 \r\nL 247.152076 119.500208 \r\nL 247.269505 119.390163 \r\nL 247.359834 119.316799 \r\nL 247.472746 119.206754 \r\nL 247.567592 119.133391 \r\nL 247.761801 119.023346 \r\nL 247.870197 118.876619 \r\nL 247.983109 118.766574 \r\nL 248.064405 118.674869 \r\nL 248.240548 118.564824 \r\nL 248.281197 118.528143 \r\nL 248.461856 118.418098 \r\nL 248.543152 118.344734 \r\nL 248.701229 118.234689 \r\nL 248.787042 118.124644 \r\nL 249.058031 118.014599 \r\nL 249.166427 117.867872 \r\nL 249.464515 117.757827 \r\nL 249.57291 117.6111 \r\nL 249.676789 117.501055 \r\nL 249.762602 117.446032 \r\nL 249.911646 117.335987 \r\nL 250.011009 117.207601 \r\nL 250.191668 117.097556 \r\nL 250.291031 116.914147 \r\nL 250.426525 116.804102 \r\nL 250.516855 116.675716 \r\nL 250.765261 116.565671 \r\nL 250.864624 116.437285 \r\nL 251.009151 116.32724 \r\nL 251.072382 116.235536 \r\nL 251.230459 116.125491 \r\nL 251.320789 116.052127 \r\nL 251.569195 115.942082 \r\nL 251.587261 115.88706 \r\nL 251.8447 115.795355 \r\nL 251.853733 115.703651 \r\nL 252.106656 115.593606 \r\nL 252.215052 115.46522 \r\nL 252.431843 115.373516 \r\nL 252.472491 115.281811 \r\nL 252.630568 115.171766 \r\nL 252.684766 115.098403 \r\nL 252.92414 114.988358 \r\nL 252.964788 114.896653 \r\nL 253.204161 114.786608 \r\nL 253.303524 114.713245 \r\nL 253.502249 114.6032 \r\nL 253.601612 114.511496 \r\nL 253.682908 114.40145 \r\nL 253.768722 114.309746 \r\nL 254.030677 114.199701 \r\nL 254.125524 114.144678 \r\nL 254.197787 114.034633 \r\nL 254.301666 113.869566 \r\nL 254.391996 113.75952 \r\nL 254.486842 113.686157 \r\nL 254.730732 113.594453 \r\nL 254.830095 113.429385 \r\nL 254.974622 113.31934 \r\nL 255.02882 113.227636 \r\nL 255.177864 113.117591 \r\nL 255.245611 112.989205 \r\nL 255.390138 112.879159 \r\nL 255.462402 112.732433 \r\nL 255.688226 112.622387 \r\nL 255.787589 112.45732 \r\nL 255.936633 112.347275 \r\nL 256.017929 112.218889 \r\nL 256.230204 112.108844 \r\nL 256.302468 111.943776 \r\nL 256.564424 111.833731 \r\nL 256.672819 111.723686 \r\nL 256.961874 111.613641 \r\nL 257.07027 111.521936 \r\nL 257.192215 111.411891 \r\nL 257.278028 111.301846 \r\nL 257.404489 111.191801 \r\nL 257.490302 111.136778 \r\nL 257.78839 111.026733 \r\nL 257.869687 110.990051 \r\nL 258.054863 110.880006 \r\nL 258.154225 110.75162 \r\nL 258.456829 110.641575 \r\nL 258.515544 110.53153 \r\nL 258.655555 110.421485 \r\nL 258.723302 110.366462 \r\nL 258.994291 110.256417 \r\nL 259.012357 110.219736 \r\nL 259.202049 110.10969 \r\nL 259.215598 110.073009 \r\nL 259.459488 109.999645 \r\nL 259.531752 109.852918 \r\nL 259.771125 109.761214 \r\nL 259.861455 109.596147 \r\nL 260.064697 109.486101 \r\nL 260.141477 109.376056 \r\nL 260.326653 109.266011 \r\nL 260.407949 109.174307 \r\nL 260.570543 109.064262 \r\nL 260.678938 108.990898 \r\nL 260.841532 108.880853 \r\nL 260.949927 108.697445 \r\nL 261.229949 108.5874 \r\nL 261.288663 108.459014 \r\nL 261.496421 108.367309 \r\nL 261.604817 108.16556 \r\nL 261.984201 108.055515 \r\nL 262.065498 107.96381 \r\nL 262.286806 107.853765 \r\nL 262.372619 107.780402 \r\nL 262.602959 107.670357 \r\nL 262.688773 107.578653 \r\nL 262.991377 107.468607 \r\nL 263.095256 107.376903 \r\nL 263.203651 107.266858 \r\nL 263.303014 107.120131 \r\nL 263.546904 107.010086 \r\nL 263.64175 106.936723 \r\nL 263.844992 106.826677 \r\nL 263.944354 106.771655 \r\nL 264.156629 106.66161 \r\nL 264.242442 106.624928 \r\nL 264.508915 106.514883 \r\nL 264.608277 106.404838 \r\nL 264.766354 106.313134 \r\nL 264.825068 106.221429 \r\nL 265.159288 106.111384 \r\nL 265.249618 106.038021 \r\nL 265.430277 105.927976 \r\nL 265.488991 105.872953 \r\nL 265.800628 105.81793 \r\nL 265.904507 105.652863 \r\nL 266.166463 105.561159 \r\nL 266.261309 105.487795 \r\nL 266.482617 105.37775 \r\nL 266.487133 105.322727 \r\nL 266.740056 105.212682 \r\nL 266.821353 105.139319 \r\nL 267.029111 105.029274 \r\nL 267.101375 104.974251 \r\nL 267.331716 104.864206 \r\nL 267.422045 104.772502 \r\nL 267.539474 104.662457 \r\nL 267.638836 104.51573 \r\nL 267.842078 104.405685 \r\nL 267.950474 104.258958 \r\nL 268.117583 104.148913 \r\nL 268.225979 104.075549 \r\nL 268.5331 103.983845 \r\nL 268.605363 103.892141 \r\nL 268.84022 103.782096 \r\nL 268.948616 103.562005 \r\nL 269.228638 103.45196 \r\nL 269.260253 103.360256 \r\nL 269.490594 103.250211 \r\nL 269.540275 103.085143 \r\nL 269.788681 102.993439 \r\nL 269.897077 102.865053 \r\nL 270.104835 102.755008 \r\nL 270.204198 102.58994 \r\nL 270.551967 102.479895 \r\nL 270.660362 102.388191 \r\nL 270.908769 102.278146 \r\nL 271.017164 102.186441 \r\nL 271.197824 102.076396 \r\nL 271.297186 101.984692 \r\nL 271.518494 101.874647 \r\nL 271.595274 101.764602 \r\nL 271.825615 101.654557 \r\nL 271.906911 101.581193 \r\nL 272.137252 101.471148 \r\nL 272.223065 101.379444 \r\nL 272.340494 101.269399 \r\nL 272.340494 101.251058 \r\nL 272.575351 101.141013 \r\nL 272.67923 101.067649 \r\nL 272.841823 100.957604 \r\nL 272.918603 100.920922 \r\nL 273.4109 100.810877 \r\nL 273.492196 100.682491 \r\nL 273.681889 100.572446 \r\nL 273.73157 100.462401 \r\nL 273.916746 100.352356 \r\nL 274.016108 100.242311 \r\nL 274.174185 100.150606 \r\nL 274.269031 100.077243 \r\nL 274.503888 99.967198 \r\nL 274.571635 99.838812 \r\nL 274.960053 99.728767 \r\nL 275.068448 99.600381 \r\nL 275.244591 99.490336 \r\nL 275.352987 99.416972 \r\nL 275.465899 99.306927 \r\nL 275.560745 99.215223 \r\nL 275.773019 99.105178 \r\nL 275.872382 98.976792 \r\nL 276.016909 98.866747 \r\nL 276.016909 98.848406 \r\nL 276.256283 98.738361 \r\nL 276.328547 98.664997 \r\nL 276.595019 98.554952 \r\nL 276.662766 98.463248 \r\nL 276.843426 98.353203 \r\nL 276.947305 98.29818 \r\nL 277.0557 98.188135 \r\nL 277.164096 98.059749 \r\nL 277.38992 97.949704 \r\nL 277.480249 97.894681 \r\nL 277.63381 97.802977 \r\nL 277.660909 97.711273 \r\nL 277.891249 97.601228 \r\nL 277.96803 97.527864 \r\nL 278.139656 97.417819 \r\nL 278.21192 97.326115 \r\nL 278.537106 97.21607 \r\nL 278.555172 97.179388 \r\nL 278.939073 97.069343 \r\nL 278.997787 96.99598 \r\nL 279.214578 96.885934 \r\nL 279.318457 96.830912 \r\nL 279.535249 96.720867 \r\nL 279.630095 96.592481 \r\nL 279.928182 96.482436 \r\nL 279.991413 96.427413 \r\nL 280.194655 96.317368 \r\nL 280.235303 96.244004 \r\nL 280.465644 96.133959 \r\nL 280.574039 96.042255 \r\nL 280.768248 95.93221 \r\nL 280.867611 95.785483 \r\nL 281.052786 95.693779 \r\nL 281.161182 95.547052 \r\nL 281.332808 95.437007 \r\nL 281.432171 95.363643 \r\nL 281.621863 95.253598 \r\nL 281.685094 95.161894 \r\nL 281.924467 95.051849 \r\nL 282.032863 94.978486 \r\nL 282.17739 94.86844 \r\nL 282.25417 94.795077 \r\nL 282.461929 94.685032 \r\nL 282.525159 94.630009 \r\nL 282.886478 94.519964 \r\nL 282.949709 94.446601 \r\nL 283.211665 94.336556 \r\nL 283.311027 94.281533 \r\nL 283.627181 94.171488 \r\nL 283.681379 94.098124 \r\nL 283.979466 93.988079 \r\nL 284.033664 93.896375 \r\nL 284.503378 93.78633 \r\nL 284.602741 93.694626 \r\nL 284.742752 93.584581 \r\nL 284.815015 93.529558 \r\nL 285.004708 93.419513 \r\nL 285.058905 93.309468 \r\nL 285.235048 93.199423 \r\nL 285.253114 93.162741 \r\nL 285.627982 93.052696 \r\nL 285.691213 92.942651 \r\nL 285.867356 92.832606 \r\nL 285.91252 92.777583 \r\nL 286.219641 92.667538 \r\nL 286.219641 92.594174 \r\nL 286.698388 92.484129 \r\nL 286.73452 92.429107 \r\nL 287.010025 92.337402 \r\nL 287.100355 92.209016 \r\nL 287.348762 92.098971 \r\nL 287.430058 91.970585 \r\nL 287.561036 91.897222 \r\nL 287.655882 91.787177 \r\nL 288.103014 91.695473 \r\nL 288.139146 91.64045 \r\nL 288.396585 91.530405 \r\nL 288.504981 91.438701 \r\nL 288.640475 91.328655 \r\nL 288.667574 91.291974 \r\nL 289.051475 91.200269 \r\nL 289.159871 91.108565 \r\nL 289.336013 91.016861 \r\nL 289.43086 90.943498 \r\nL 289.665717 90.833452 \r\nL 289.75153 90.77843 \r\nL 289.98187 90.668385 \r\nL 290.081233 90.521658 \r\nL 290.329639 90.411613 \r\nL 290.401903 90.283227 \r\nL 290.632244 90.173182 \r\nL 290.740639 90.081477 \r\nL 290.961947 89.971432 \r\nL 291.043243 89.788024 \r\nL 291.241969 89.696319 \r\nL 291.345848 89.567933 \r\nL 291.449727 89.457888 \r\nL 291.553606 89.402866 \r\nL 291.756848 89.292821 \r\nL 291.865243 89.201116 \r\nL 292.036869 89.091071 \r\nL 292.136232 88.962685 \r\nL 292.330441 88.85264 \r\nL 292.375606 88.815958 \r\nL 292.605946 88.724254 \r\nL 292.655627 88.595868 \r\nL 292.840803 88.485823 \r\nL 292.944682 88.375778 \r\nL 293.193089 88.265733 \r\nL 293.269869 88.174029 \r\nL 293.427946 88.063983 \r\nL 293.536341 87.99062 \r\nL 293.649253 87.917257 \r\nL 293.685385 87.825552 \r\nL 293.969924 87.715507 \r\nL 294.069286 87.587121 \r\nL 294.29511 87.477076 \r\nL 294.37189 87.385372 \r\nL 294.633846 87.275327 \r\nL 294.710626 87.183622 \r\nL 295.139692 87.073577 \r\nL 295.243571 87.018555 \r\nL 295.34745 86.90851 \r\nL 295.433264 86.853487 \r\nL 295.622956 86.743442 \r\nL 295.636505 86.688419 \r\nL 295.92556 86.578374 \r\nL 296.033956 86.449988 \r\nL 296.544318 86.339943 \r\nL 296.575933 86.248239 \r\nL 296.797241 86.138194 \r\nL 296.90112 85.954785 \r\nL 297.361801 85.84474 \r\nL 297.406966 85.753036 \r\nL 297.596658 85.642991 \r\nL 297.696021 85.532945 \r\nL 298.134119 85.4229 \r\nL 298.215416 85.386219 \r\nL 298.378009 85.276174 \r\nL 298.477372 85.221151 \r\nL 298.667064 85.111106 \r\nL 298.76191 85.019402 \r\nL 299.073548 84.909356 \r\nL 299.159361 84.854334 \r\nL 299.389701 84.744289 \r\nL 299.443899 84.652584 \r\nL 299.606492 84.542539 \r\nL 299.665207 84.487517 \r\nL 300.026525 84.377472 \r\nL 300.080723 84.322449 \r\nL 300.311064 84.212404 \r\nL 300.378811 84.139041 \r\nL 300.816909 84.028995 \r\nL 300.911756 83.937291 \r\nL 301.056283 83.827246 \r\nL 301.078865 83.772223 \r\nL 301.363404 83.662178 \r\nL 301.462766 83.552133 \r\nL 301.733755 83.442088 \r\nL 301.833118 83.387065 \r\nL 301.918931 83.27702 \r\nL 302.027327 83.166975 \r\nL 302.162821 83.05693 \r\nL 302.2667 82.946885 \r\nL 302.501557 82.83684 \r\nL 302.501557 82.818499 \r\nL 302.862876 82.708454 \r\nL 302.935139 82.63509 \r\nL 303.237744 82.525045 \r\nL 303.323557 82.433341 \r\nL 303.553897 82.323296 \r\nL 303.662293 82.176569 \r\nL 303.910699 82.084865 \r\nL 303.910699 82.048183 \r\nL 304.177172 81.938138 \r\nL 304.235886 81.828093 \r\nL 304.466227 81.718048 \r\nL 304.543007 81.644684 \r\nL 304.85916 81.534639 \r\nL 304.899809 81.497957 \r\nL 305.161765 81.387912 \r\nL 305.243061 81.296208 \r\nL 305.550182 81.186163 \r\nL 305.658578 81.076118 \r\nL 305.947632 80.966073 \r\nL 305.988281 80.929391 \r\nL 306.448962 80.837687 \r\nL 306.539292 80.782664 \r\nL 306.652204 80.672619 \r\nL 306.742533 80.599256 \r\nL 307.036105 80.48921 \r\nL 307.130951 80.397506 \r\nL 307.47872 80.287461 \r\nL 307.582599 80.250779 \r\nL 307.767775 80.140734 \r\nL 307.871654 80.067371 \r\nL 308.129093 79.957326 \r\nL 308.223939 79.82894 \r\nL 308.413631 79.718895 \r\nL 308.522027 79.663872 \r\nL 308.720752 79.553827 \r\nL 308.788499 79.480463 \r\nL 308.991741 79.370418 \r\nL 309.045939 79.297055 \r\nL 309.366609 79.18701 \r\nL 309.470488 79.095306 \r\nL 309.628565 78.98526 \r\nL 309.732444 78.875215 \r\nL 310.202158 78.76517 \r\nL 310.283455 78.710148 \r\nL 310.545411 78.600102 \r\nL 310.57251 78.526739 \r\nL 310.938345 78.416694 \r\nL 311.037707 78.306649 \r\nL 311.227399 78.196604 \r\nL 311.326762 78.068218 \r\nL 311.484839 77.958173 \r\nL 311.530004 77.884809 \r\nL 311.760344 77.774764 \r\nL 311.810025 77.738082 \r\nL 312.071981 77.628037 \r\nL 312.071981 77.591355 \r\nL 312.415234 77.48131 \r\nL 312.51008 77.407947 \r\nL 312.889465 77.297902 \r\nL 312.984311 77.206198 \r\nL 313.372728 77.096152 \r\nL 313.444992 76.949426 \r\nL 313.693398 76.83938 \r\nL 313.797277 76.766017 \r\nL 314.172145 76.655972 \r\nL 314.271508 76.600949 \r\nL 314.632826 76.490904 \r\nL 314.736706 76.417541 \r\nL 314.867683 76.325837 \r\nL 314.939947 76.160769 \r\nL 315.20642 76.050724 \r\nL 315.305782 75.940679 \r\nL 315.816145 75.830633 \r\nL 315.816145 75.812293 \r\nL 316.218111 75.702247 \r\nL 316.218111 75.683907 \r\nL 316.791705 75.573861 \r\nL 316.841386 75.482157 \r\nL 317.035595 75.372112 \r\nL 317.116891 75.33543 \r\nL 317.302067 75.243726 \r\nL 317.405946 75.078658 \r\nL 317.758232 74.968613 \r\nL 317.857594 74.840227 \r\nL 318.020188 74.730182 \r\nL 318.065352 74.67516 \r\nL 318.503451 74.565115 \r\nL 318.521517 74.528433 \r\nL 318.787989 74.418388 \r\nL 318.846704 74.381706 \r\nL 319.027363 74.271661 \r\nL 319.086077 74.161616 \r\nL 319.307385 74.069911 \r\nL 319.379649 73.941525 \r\nL 319.560308 73.83148 \r\nL 319.646121 73.721435 \r\nL 319.962275 73.61139 \r\nL 320.052604 73.427982 \r\nL 320.278428 73.317936 \r\nL 320.377791 73.262914 \r\nL 320.698461 73.152869 \r\nL 320.770725 73.097846 \r\nL 320.874604 73.006142 \r\nL 320.955901 72.877756 \r\nL 321.141076 72.767711 \r\nL 321.222373 72.694347 \r\nL 321.470779 72.584302 \r\nL 321.570142 72.492598 \r\nL 321.750801 72.400894 \r\nL 321.827581 72.309189 \r\nL 322.252131 72.199144 \r\nL 322.315362 72.125781 \r\nL 322.563768 72.015736 \r\nL 322.672164 71.905691 \r\nL 323.078647 71.795645 \r\nL 323.110262 71.740623 \r\nL 323.367702 71.630578 \r\nL 323.421899 71.575555 \r\nL 323.706438 71.46551 \r\nL 323.783218 71.428828 \r\nL 324.198734 71.318783 \r\nL 324.30713 71.135375 \r\nL 324.600701 71.02533 \r\nL 324.700064 70.915284 \r\nL 324.998152 70.805239 \r\nL 325.074932 70.750217 \r\nL 325.377536 70.640172 \r\nL 325.43625 70.585149 \r\nL 325.820151 70.475104 \r\nL 325.824668 70.438422 \r\nL 326.253733 70.328377 \r\nL 326.285349 70.291695 \r\nL 326.447942 70.18165 \r\nL 326.506656 70.089946 \r\nL 326.714414 69.979901 \r\nL 326.804744 69.888197 \r\nL 327.0667 69.778151 \r\nL 327.175096 69.704788 \r\nL 327.459634 69.613084 \r\nL 327.504799 69.558061 \r\nL 327.897733 69.448016 \r\nL 327.979029 69.337971 \r\nL 328.308732 69.227926 \r\nL 328.417128 69.172903 \r\nL 328.733282 69.062858 \r\nL 328.832644 69.007836 \r\nL 329.397205 68.89779 \r\nL 329.5056 68.824427 \r\nL 329.817237 68.714382 \r\nL 329.925633 68.585996 \r\nL 330.061127 68.475951 \r\nL 330.16049 68.402587 \r\nL 330.332116 68.292542 \r\nL 330.368248 68.23752 \r\nL 330.539874 68.127475 \r\nL 330.643753 67.944066 \r\nL 330.783764 67.834021 \r\nL 330.846995 67.760658 \r\nL 331.375423 67.650612 \r\nL 331.45672 67.577249 \r\nL 331.655445 67.467204 \r\nL 331.655445 67.448863 \r\nL 331.908368 67.338818 \r\nL 332.007731 67.210432 \r\nL 332.396148 67.100387 \r\nL 332.504544 67.008682 \r\nL 332.838763 66.898637 \r\nL 332.888445 66.861956 \r\nL 333.294928 66.751911 \r\nL 333.380741 66.586843 \r\nL 333.507203 66.476798 \r\nL 333.615598 66.403434 \r\nL 333.945301 66.293389 \r\nL 334.04918 66.238367 \r\nL 334.446631 66.128321 \r\nL 334.482763 66.09164 \r\nL 334.812466 65.981595 \r\nL 334.835048 65.944913 \r\nL 335.214433 65.834868 \r\nL 335.255081 65.761504 \r\nL 335.480905 65.651459 \r\nL 335.553169 65.578096 \r\nL 335.882872 65.468051 \r\nL 335.991268 65.394687 \r\nL 336.149344 65.284642 \r\nL 336.24419 65.211279 \r\nL 336.465498 65.101234 \r\nL 336.48808 65.046211 \r\nL 336.935212 64.936166 \r\nL 337.016509 64.844462 \r\nL 337.228783 64.734417 \r\nL 337.305564 64.642712 \r\nL 337.63075 64.532667 \r\nL 337.63075 64.514326 \r\nL 338.13208 64.404281 \r\nL 338.240475 64.349259 \r\nL 338.385003 64.239213 \r\nL 338.493398 64.129168 \r\nL 338.674058 64.019123 \r\nL 338.741805 63.890737 \r\nL 339.09409 63.780692 \r\nL 339.143772 63.707329 \r\nL 339.369596 63.615624 \r\nL 339.387662 63.560602 \r\nL 339.771563 63.450557 \r\nL 339.861892 63.395534 \r\nL 340.119332 63.285489 \r\nL 340.214178 63.212126 \r\nL 340.412903 63.10208 \r\nL 340.462584 63.047058 \r\nL 340.692925 62.955354 \r\nL 340.80132 62.790286 \r\nL 341.112958 62.680241 \r\nL 341.13554 62.643559 \r\nL 341.329749 62.551855 \r\nL 341.411045 62.496832 \r\nL 341.767847 62.386787 \r\nL 341.876243 62.295083 \r\nL 342.1111 62.185038 \r\nL 342.205946 62.130015 \r\nL 342.738891 62.01997 \r\nL 342.738891 62.001629 \r\nL 343.082144 61.891584 \r\nL 343.131825 61.854902 \r\nL 343.520242 61.744857 \r\nL 343.520242 61.726516 \r\nL 343.718967 61.616471 \r\nL 343.822846 61.543108 \r\nL 344.035121 61.433063 \r\nL 344.075769 61.396381 \r\nL 344.405473 61.286336 \r\nL 344.477736 61.231313 \r\nL 344.70356 61.121268 \r\nL 344.766791 61.084586 \r\nL 344.956483 60.974541 \r\nL 345.033264 60.901178 \r\nL 345.272637 60.791133 \r\nL 345.28167 60.73611 \r\nL 345.787516 60.626065 \r\nL 345.855263 60.460997 \r\nL 346.022373 60.350952 \r\nL 346.10367 60.240907 \r\nL 346.469505 60.130862 \r\nL 346.573384 60.057499 \r\nL 346.726944 59.947454 \r\nL 346.82179 59.87409 \r\nL 347.002449 59.764045 \r\nL 347.097296 59.690682 \r\nL 347.413449 59.580636 \r\nL 347.463131 59.525614 \r\nL 347.661856 59.43391 \r\nL 347.756702 59.323864 \r\nL 347.892196 59.213819 \r\nL 348.000592 59.122115 \r\nL 348.248998 59.01207 \r\nL 348.307713 58.957047 \r\nL 348.637416 58.847002 \r\nL 348.745811 58.700275 \r\nL 349.052932 58.59023 \r\nL 349.052932 58.571889 \r\nL 349.491031 58.461844 \r\nL 349.58136 58.37014 \r\nL 349.879448 58.260095 \r\nL 349.987844 58.095027 \r\nL 350.475624 57.984982 \r\nL 350.475624 57.9483 \r\nL 351.013085 57.838255 \r\nL 351.013085 57.819914 \r\nL 351.324722 57.709869 \r\nL 351.410535 57.618165 \r\nL 351.767337 57.50812 \r\nL 351.826052 57.471438 \r\nL 352.119623 57.361393 \r\nL 352.191887 57.233007 \r\nL 352.426744 57.122962 \r\nL 352.494491 57.012917 \r\nL 352.756447 56.902872 \r\nL 352.824194 56.829508 \r\nL 353.411337 56.719463 \r\nL 353.4836 56.664441 \r\nL 353.835886 56.554395 \r\nL 353.867501 56.499373 \r\nL 354.147523 56.389328 \r\nL 354.255919 56.315964 \r\nL 354.54949 56.205919 \r\nL 354.62627 56.077533 \r\nL 354.874677 55.967488 \r\nL 354.969523 55.930806 \r\nL 355.29471 55.839102 \r\nL 355.389556 55.692375 \r\nL 355.552149 55.58233 \r\nL 355.642479 55.472285 \r\nL 355.899918 55.36224 \r\nL 355.990248 55.270536 \r\nL 356.229621 55.16049 \r\nL 356.301885 55.105468 \r\nL 356.523192 54.995423 \r\nL 356.609006 54.922059 \r\nL 356.866445 54.812014 \r\nL 356.866445 54.775333 \r\nL 357.214214 54.665287 \r\nL 357.30906 54.610265 \r\nL 357.503269 54.50022 \r\nL 357.521335 54.463538 \r\nL 357.896203 54.353493 \r\nL 357.968467 54.29847 \r\nL 358.29817 54.188425 \r\nL 358.397532 54.151743 \r\nL 358.754334 54.041698 \r\nL 358.831115 53.913312 \r\nL 359.1834 53.803267 \r\nL 359.246631 53.729904 \r\nL 359.576334 53.619859 \r\nL 359.680213 53.528154 \r\nL 359.933136 53.418109 \r\nL 360.037015 53.363087 \r\nL 360.32607 53.253042 \r\nL 360.40285 53.142996 \r\nL 360.809333 53.032951 \r\nL 360.917729 52.977929 \r\nL 361.283564 52.867884 \r\nL 361.360344 52.831202 \r\nL 361.541003 52.721157 \r\nL 361.640366 52.629453 \r\nL 361.902322 52.519407 \r\nL 361.992652 52.446044 \r\nL 362.268157 52.335999 \r\nL 362.313322 52.280976 \r\nL 362.683673 52.207613 \r\nL 362.783036 52.079227 \r\nL 363.112739 51.969182 \r\nL 363.112739 51.950841 \r\nL 363.492123 51.840796 \r\nL 363.58697 51.767432 \r\nL 363.880541 51.657387 \r\nL 363.934739 51.565683 \r\nL 364.246376 51.455638 \r\nL 364.250892 51.418956 \r\nL 364.603178 51.308911 \r\nL 364.707057 51.253888 \r\nL 364.964496 51.143843 \r\nL 365.009661 51.088821 \r\nL 365.339364 50.997117 \r\nL 365.416145 50.887071 \r\nL 365.723265 50.777026 \r\nL 365.795529 50.722004 \r\nL 366.233628 50.611959 \r\nL 366.33299 50.556936 \r\nL 366.75754 50.446891 \r\nL 366.856902 50.410209 \r\nL 367.222737 50.300164 \r\nL 367.222737 50.281823 \r\nL 367.633737 50.171778 \r\nL 367.651803 50.116756 \r\nL 368.049253 50.00671 \r\nL 368.126034 49.933347 \r\nL 368.329275 49.823302 \r\nL 368.387989 49.731598 \r\nL 368.604781 49.621552 \r\nL 368.604781 49.584871 \r\nL 368.893835 49.474826 \r\nL 368.993198 49.383121 \r\nL 369.237088 49.273076 \r\nL 369.318385 49.218054 \r\nL 369.639055 49.108009 \r\nL 369.688736 49.052986 \r\nL 370.113285 48.942941 \r\nL 370.153934 48.906259 \r\nL 370.578483 48.796214 \r\nL 370.682362 48.722851 \r\nL 371.106911 48.612805 \r\nL 371.179175 48.576124 \r\nL 371.825032 48.466079 \r\nL 371.883746 48.429397 \r\nL 372.502504 48.319352 \r\nL 372.502504 48.301011 \r\nL 372.972218 48.190966 \r\nL 373.067064 48.099262 \r\nL 373.658723 47.989216 \r\nL 373.703888 47.897512 \r\nL 374.105855 47.787467 \r\nL 374.169086 47.732444 \r\nL 374.742679 47.622399 \r\nL 374.801393 47.585718 \r\nL 375.239492 47.475672 \r\nL 375.329822 47.42065 \r\nL 375.682107 47.310605 \r\nL 375.772437 47.255582 \r\nL 376.192469 47.145537 \r\nL 376.246667 47.053833 \r\nL 377.073183 46.943788 \r\nL 377.127381 46.907106 \r\nL 377.538381 46.815402 \r\nL 377.637744 46.742038 \r\nL 378.211337 46.631993 \r\nL 378.301666 46.55863 \r\nL 378.757831 46.448585 \r\nL 378.757831 46.411903 \r\nL 379.168831 46.301858 \r\nL 379.254644 46.265176 \r\nL 379.674677 46.155131 \r\nL 379.728875 46.100108 \r\nL 380.153424 45.990063 \r\nL 380.257303 45.935041 \r\nL 380.690885 45.824996 \r\nL 380.794764 45.769973 \r\nL 380.894127 45.678269 \r\nL 380.957357 45.604905 \r\nL 381.431588 45.49486 \r\nL 381.526434 45.458178 \r\nL 382.294236 45.348133 \r\nL 382.371016 45.311452 \r\nL 382.741368 45.201407 \r\nL 382.831697 45.164725 \r\nL 383.283345 45.05468 \r\nL 383.391741 44.999657 \r\nL 383.75306 44.889612 \r\nL 383.82984 44.834589 \r\nL 384.06018 44.724544 \r\nL 384.132444 44.651181 \r\nL 384.453114 44.541136 \r\nL 384.457631 44.504454 \r\nL 384.827982 44.394409 \r\nL 384.913795 44.357727 \r\nL 385.184784 44.247682 \r\nL 385.284147 44.19266 \r\nL 385.749344 44.082614 \r\nL 385.749344 44.064274 \r\nL 386.083564 43.954228 \r\nL 386.169377 43.825842 \r\nL 386.761036 43.715797 \r\nL 386.783619 43.679116 \r\nL 387.208168 43.56907 \r\nL 387.298498 43.477366 \r\nL 387.524322 43.367321 \r\nL 387.524322 43.34898 \r\nL 387.835959 43.238935 \r\nL 387.872091 43.202253 \r\nL 388.748288 43.092208 \r\nL 388.757321 43.055527 \r\nL 389.150255 42.945481 \r\nL 389.249618 42.853777 \r\nL 389.466409 42.743732 \r\nL 389.507057 42.70705 \r\nL 389.705782 42.615346 \r\nL 389.746431 42.541983 \r\nL 390.130331 42.431937 \r\nL 390.238727 42.376915 \r\nL 390.41487 42.26687 \r\nL 390.500683 42.211847 \r\nL 390.943298 42.101802 \r\nL 390.952331 42.06512 \r\nL 391.327199 41.973416 \r\nL 391.435595 41.900053 \r\nL 391.720133 41.790008 \r\nL 391.720133 41.771667 \r\nL 392.230495 41.661622 \r\nL 392.28921 41.588258 \r\nL 392.935066 41.478213 \r\nL 392.998297 41.423191 \r\nL 393.436396 41.313145 \r\nL 393.436396 41.294805 \r\nL 393.90611 41.184759 \r\nL 393.991923 41.129737 \r\nL 394.24033 41.019692 \r\nL 394.24033 41.001351 \r\nL 395.012648 40.891306 \r\nL 395.116527 40.781261 \r\nL 395.753351 40.689556 \r\nL 395.85723 40.634534 \r\nL 396.724394 40.524489 \r\nL 396.83279 40.432784 \r\nL 397.112812 40.322739 \r\nL 397.203142 40.267717 \r\nL 397.609625 40.157672 \r\nL 397.686405 40.12099 \r\nL 397.934812 40.010945 \r\nL 397.97546 39.9009 \r\nL 398.472273 39.790854 \r\nL 398.567119 39.69915 \r\nL 398.982635 39.589105 \r\nL 399.091031 39.534082 \r\nL 399.92658 39.424037 \r\nL 399.994327 39.387356 \r\nL 400.445975 39.277311 \r\nL 400.509206 39.222288 \r\nL 400.992469 39.112243 \r\nL 401.042151 39.075561 \r\nL 401.398953 38.965516 \r\nL 401.4667 38.873812 \r\nL 402.135139 38.763767 \r\nL 402.239018 38.690403 \r\nL 402.6997 38.580358 \r\nL 402.77648 38.543676 \r\nL 403.214578 38.433631 \r\nL 403.313941 38.323586 \r\nL 403.499117 38.213541 \r\nL 403.575897 38.176859 \r\nL 404.208204 38.066814 \r\nL 404.271435 38.011792 \r\nL 404.80438 37.901746 \r\nL 404.872127 37.828383 \r\nL 405.472819 37.718338 \r\nL 405.549599 37.644974 \r\nL 406.132225 37.534929 \r\nL 406.199973 37.498248 \r\nL 406.529676 37.388203 \r\nL 406.529676 37.369862 \r\nL 407.112302 37.259817 \r\nL 407.112302 37.241476 \r\nL 407.491686 37.131431 \r\nL 407.600082 37.058067 \r\nL 408.083345 36.948022 \r\nL 408.169159 36.856318 \r\nL 408.941477 36.746273 \r\nL 409.009224 36.69125 \r\nL 409.546685 36.581205 \r\nL 409.546685 36.562864 \r\nL 409.930586 36.452819 \r\nL 409.998334 36.361115 \r\nL 410.517729 36.25107 \r\nL 410.517729 36.232729 \r\nL 411.529421 36.122684 \r\nL 411.529421 36.104343 \r\nL 412.224959 35.994298 \r\nL 412.310772 35.902593 \r\nL 412.843717 35.792548 \r\nL 412.938563 35.737526 \r\nL 413.322464 35.62748 \r\nL 413.412794 35.572458 \r\nL 413.728947 35.462413 \r\nL 413.823793 35.352368 \r\nL 414.334156 35.242323 \r\nL 414.429002 35.132277 \r\nL 414.849035 35.022232 \r\nL 414.849035 35.003891 \r\nL 415.476826 34.893846 \r\nL 415.476826 34.875505 \r\nL 416.140748 34.783801 \r\nL 416.203979 34.728779 \r\nL 416.953715 34.618733 \r\nL 417.062111 34.563711 \r\nL 417.540858 34.453666 \r\nL 417.595056 34.416984 \r\nL 418.091869 34.306939 \r\nL 418.159616 34.270257 \r\nL 418.755791 34.160212 \r\nL 418.855154 34.10519 \r\nL 419.537143 33.995144 \r\nL 419.573274 33.940122 \r\nL 420.232681 33.830077 \r\nL 420.268813 33.793395 \r\nL 420.553351 33.68335 \r\nL 420.557867 33.646668 \r\nL 421.212757 33.536623 \r\nL 421.316636 33.481601 \r\nL 421.668922 33.371555 \r\nL 421.777317 33.298192 \r\nL 422.156702 33.188147 \r\nL 422.251548 33.133124 \r\nL 422.400592 33.04142 \r\nL 422.414141 32.986397 \r\nL 422.901921 32.876352 \r\nL 422.947086 32.839671 \r\nL 423.615525 32.729625 \r\nL 423.629075 32.692944 \r\nL 424.012976 32.582899 \r\nL 424.121371 32.546217 \r\nL 424.776261 32.436172 \r\nL 424.884657 32.344468 \r\nL 425.182744 32.252763 \r\nL 425.209843 32.197741 \r\nL 425.399536 32.106036 \r\nL 425.453733 32.014332 \r\nL 426.280249 31.904287 \r\nL 426.366063 31.867605 \r\nL 426.772546 31.75756 \r\nL 426.786095 31.720878 \r\nL 428.032644 31.610833 \r\nL 428.12749 31.53747 \r\nL 428.669468 31.427425 \r\nL 428.692051 31.390743 \r\nL 429.252094 31.280698 \r\nL 429.252094 31.262357 \r\nL 429.929567 31.152312 \r\nL 429.929567 31.133971 \r\nL 430.588973 31.023926 \r\nL 430.643171 30.968903 \r\nL 430.932225 30.858858 \r\nL 431.040621 30.767154 \r\nL 431.356775 30.657109 \r\nL 431.410973 30.602086 \r\nL 431.998115 30.492041 \r\nL 431.998115 30.4737 \r\nL 432.332335 30.363655 \r\nL 432.382016 30.326974 \r\nL 433.032389 30.216928 \r\nL 433.10917 30.161906 \r\nL 433.574367 30.070202 \r\nL 433.574367 30.03352 \r\nL 434.427982 29.923475 \r\nL 434.527345 29.868452 \r\nL 435.557103 29.758407 \r\nL 435.588718 29.703385 \r\nL 436.049399 29.593339 \r\nL 436.126179 29.556658 \r\nL 436.916563 29.446613 \r\nL 436.993344 29.39159 \r\nL 437.476607 29.281545 \r\nL 437.508223 29.226522 \r\nL 437.788244 29.116477 \r\nL 437.801794 29.079795 \r\nL 438.321189 28.96975 \r\nL 438.321189 28.951409 \r\nL 438.8722 28.841364 \r\nL 438.8722 28.823023 \r\nL 439.328365 28.712978 \r\nL 439.418694 28.676297 \r\nL 440.141331 28.566252 \r\nL 440.213595 28.52957 \r\nL 440.723957 28.419525 \r\nL 440.73299 28.382843 \r\nL 441.830495 28.272798 \r\nL 441.907276 28.236116 \r\nL 442.593781 28.126071 \r\nL 442.593781 28.10773 \r\nL 443.090594 27.997685 \r\nL 443.126726 27.942662 \r\nL 443.623539 27.832617 \r\nL 443.623539 27.814276 \r\nL 444.341659 27.704231 \r\nL 444.413923 27.630868 \r\nL 445.321736 27.520823 \r\nL 445.393999 27.484141 \r\nL 446.428274 27.374096 \r\nL 446.446339 27.337414 \r\nL 447.24124 27.227369 \r\nL 447.24124 27.209028 \r\nL 448.30713 27.098983 \r\nL 448.320679 27.062301 \r\nL 448.754262 26.952256 \r\nL 448.754262 26.933915 \r\nL 449.874349 26.82387 \r\nL 449.955646 26.768848 \r\nL 450.619568 26.658803 \r\nL 450.624085 26.622121 \r\nL 451.56803 26.512076 \r\nL 451.626744 26.475394 \r\nL 452.358414 26.365349 \r\nL 452.371963 26.328667 \r\nL 452.913941 26.236963 \r\nL 453.01782 26.18194 \r\nL 453.636578 26.071895 \r\nL 453.636578 26.053554 \r\nL 454.395347 25.943509 \r\nL 454.426962 25.906828 \r\nL 455.014105 25.796783 \r\nL 455.090885 25.74176 \r\nL 456.418731 25.631715 \r\nL 456.513577 25.576692 \r\nL 457.570433 25.484988 \r\nL 457.669796 25.429965 \r\nL 458.916345 25.31992 \r\nL 459.02474 25.283239 \r\nL 460.465498 25.173193 \r\nL 460.569377 25.118171 \r\nL 461.341696 25.008126 \r\nL 461.341696 24.989785 \r\nL 462.141113 24.87974 \r\nL 462.141113 24.861399 \r\nL 463.685749 24.751354 \r\nL 463.685749 24.733013 \r\nL 464.40387 24.622968 \r\nL 464.40387 24.604627 \r\nL 465.248452 24.494582 \r\nL 465.248452 24.476241 \r\nL 466.350474 24.366196 \r\nL 466.458869 24.329514 \r\nL 467.158924 24.219469 \r\nL 467.231187 24.182787 \r\nL 468.369341 24.072742 \r\nL 468.369341 24.054401 \r\nL 469.728802 23.944356 \r\nL 469.823648 23.907674 \r\nL 470.108186 23.81597 \r\nL 470.108186 23.779289 \r\nL 471.133427 23.669243 \r\nL 471.133427 23.650903 \r\nL 472.366427 23.540857 \r\nL 472.366427 23.522517 \r\nL 473.870415 23.412471 \r\nL 473.911064 23.37579 \r\nL 474.529822 23.265745 \r\nL 474.597569 23.229063 \r\nL 475.505382 23.119018 \r\nL 475.505382 23.100677 \r\nL 477.072601 22.990632 \r\nL 477.072601 22.972291 \r\nL 477.786205 22.862246 \r\nL 477.835886 22.788882 \r\nL 479.077918 22.678837 \r\nL 479.077918 22.660496 \r\nL 479.863786 22.550451 \r\nL 479.863786 22.53211 \r\nL 481.132918 22.422065 \r\nL 481.132918 22.403724 \r\nL 482.239455 22.293679 \r\nL 482.325269 22.201975 \r\nL 483.535686 22.09193 \r\nL 483.585367 22.055248 \r\nL 485.550036 21.945203 \r\nL 485.550036 21.926862 \r\nL 487.311464 21.816817 \r\nL 487.311464 21.798476 \r\nL 489.434211 21.688431 \r\nL 489.461309 21.651749 \r\nL 491.195638 21.541704 \r\nL 491.195638 21.523363 \r\nL 493.35 21.45 \r\nL 493.35 21.45 \r\n\" style=\"fill:none;stroke:#4c72b0;stroke-linecap:round;stroke-width:1.5;\"/>\r\n   </g>\r\n   <g id=\"line2d_14\">\r\n    <path clip-path=\"url(#pd79d4fe22e)\" d=\"M 46.95 456.33 \r\nL 493.35 21.45 \r\n\" style=\"fill:none;stroke:#c44e52;stroke-dasharray:5.55,2.4;stroke-dashoffset:0;stroke-width:1.5;\"/>\r\n   </g>\r\n   <g id=\"patch_3\">\r\n    <path d=\"M 46.95 456.33 \r\nL 46.95 21.45 \r\n\" style=\"fill:none;stroke:#ffffff;stroke-linecap:square;stroke-linejoin:miter;stroke-width:1.25;\"/>\r\n   </g>\r\n   <g id=\"patch_4\">\r\n    <path d=\"M 493.35 456.33 \r\nL 493.35 21.45 \r\n\" style=\"fill:none;stroke:#ffffff;stroke-linecap:square;stroke-linejoin:miter;stroke-width:1.25;\"/>\r\n   </g>\r\n   <g id=\"patch_5\">\r\n    <path d=\"M 46.95 456.33 \r\nL 493.35 456.33 \r\n\" style=\"fill:none;stroke:#ffffff;stroke-linecap:square;stroke-linejoin:miter;stroke-width:1.25;\"/>\r\n   </g>\r\n   <g id=\"patch_6\">\r\n    <path d=\"M 46.95 21.45 \r\nL 493.35 21.45 \r\n\" style=\"fill:none;stroke:#ffffff;stroke-linecap:square;stroke-linejoin:miter;stroke-width:1.25;\"/>\r\n   </g>\r\n   <g id=\"text_15\">\r\n    <!-- ROC -->\r\n    <g style=\"fill:#262626;\" transform=\"translate(261.15 15.45)scale(0.12 -0.12)\">\r\n     <defs>\r\n      <path d=\"M 46.09375 35.546875 \r\nQ 46.09375 17.1875 40.421875 9.171875 \r\nQ 34.765625 1.171875 24.609375 1.171875 \r\nQ 14.453125 1.171875 8.59375 9.171875 \r\nQ 2.734375 17.1875 2.734375 35.546875 \r\nQ 2.734375 53.90625 8.59375 61.71875 \r\nQ 14.453125 69.53125 24.609375 69.53125 \r\nQ 34.765625 69.53125 40.421875 61.71875 \r\nQ 46.09375 53.90625 46.09375 35.546875 \r\nz\r\nM 36.71875 35.546875 \r\nQ 36.71875 51.953125 33.203125 57.03125 \r\nQ 29.6875 62.109375 24.609375 62.109375 \r\nQ 19.53125 62.109375 15.8125 57.03125 \r\nQ 12.109375 51.953125 12.109375 35.546875 \r\nQ 12.109375 19.140625 15.8125 13.859375 \r\nQ 19.53125 8.59375 24.609375 8.59375 \r\nQ 29.6875 8.59375 33.203125 13.859375 \r\nQ 36.71875 19.140625 36.71875 35.546875 \r\nz\r\n\" id=\"SimHei-79\"/>\r\n      <path d=\"M 46.484375 28.515625 \r\nQ 46.09375 13.671875 40.234375 7.421875 \r\nQ 34.375 1.171875 26.171875 1.171875 \r\nQ 16.796875 1.171875 10.15625 8.78125 \r\nQ 3.515625 16.40625 3.515625 33.203125 \r\nQ 3.515625 51.5625 9.953125 60.546875 \r\nQ 16.40625 69.53125 26.5625 69.53125 \r\nQ 35.15625 69.53125 40.8125 63.078125 \r\nQ 46.484375 56.640625 46.09375 44.921875 \r\nL 37.5 44.921875 \r\nQ 37.5 53.515625 34.765625 57.8125 \r\nQ 32.03125 62.109375 26.5625 62.109375 \r\nQ 20.3125 62.109375 16.59375 55.65625 \r\nQ 12.890625 49.21875 12.890625 33.984375 \r\nQ 12.890625 19.921875 16.59375 14.25 \r\nQ 20.3125 8.59375 26.171875 8.59375 \r\nQ 30.46875 8.59375 33.984375 12.6875 \r\nQ 37.5 16.796875 37.5 28.515625 \r\nz\r\n\" id=\"SimHei-67\"/>\r\n     </defs>\r\n     <use xlink:href=\"#SimHei-82\"/>\r\n     <use x=\"50\" xlink:href=\"#SimHei-79\"/>\r\n     <use x=\"100\" xlink:href=\"#SimHei-67\"/>\r\n    </g>\r\n   </g>\r\n   <g id=\"legend_1\">\r\n    <g id=\"patch_7\">\r\n     <path d=\"M 54.65 44.825 \r\nL 177.85 44.825 \r\nQ 180.05 44.825 180.05 42.625 \r\nL 180.05 29.15 \r\nQ 180.05 26.95 177.85 26.95 \r\nL 54.65 26.95 \r\nQ 52.45 26.95 52.45 29.15 \r\nL 52.45 42.625 \r\nQ 52.45 44.825 54.65 44.825 \r\nz\r\n\" style=\"fill:#eaeaf2;opacity:0.8;stroke:#cccccc;stroke-linejoin:miter;\"/>\r\n    </g>\r\n    <g id=\"line2d_15\">\r\n     <path d=\"M 56.85 35.2 \r\nL 78.85 35.2 \r\n\" style=\"fill:none;stroke:#4c72b0;stroke-linecap:round;stroke-width:1.5;\"/>\r\n    </g>\r\n    <g id=\"line2d_16\"/>\r\n    <g id=\"text_16\">\r\n     <!-- Val AUC = 0.7315 -->\r\n     <g style=\"fill:#262626;\" transform=\"translate(87.65 39.05)scale(0.11 -0.11)\">\r\n      <defs>\r\n       <path d=\"M 47.65625 68.75 \r\nL 28.125 1.171875 \r\nL 20.3125 1.171875 \r\nL 0.78125 68.75 \r\nL 10.15625 68.75 \r\nL 23.828125 17.578125 \r\nL 24.609375 17.578125 \r\nL 38.28125 68.75 \r\nz\r\n\" id=\"SimHei-86\"/>\r\n       <path d=\"M 48.046875 1.953125 \r\nL 38.671875 1.953125 \r\nL 33.203125 22.65625 \r\nL 16.015625 22.65625 \r\nL 10.546875 1.953125 \r\nL 1.171875 1.953125 \r\nL 20.703125 69.53125 \r\nL 28.515625 69.53125 \r\nz\r\nM 31.25 30.078125 \r\nL 25 53.90625 \r\nL 24.21875 53.90625 \r\nL 17.96875 30.078125 \r\nz\r\n\" id=\"SimHei-65\"/>\r\n       <path d=\"M 44.921875 21.484375 \r\nQ 44.921875 12.109375 40.03125 6.640625 \r\nQ 35.15625 1.171875 24.609375 1.171875 \r\nQ 14.0625 1.171875 9.171875 6.640625 \r\nQ 4.296875 12.109375 4.296875 21.484375 \r\nL 4.296875 68.75 \r\nL 13.28125 68.75 \r\nL 13.28125 21.484375 \r\nQ 13.28125 14.84375 16.40625 11.71875 \r\nQ 19.53125 8.59375 24.609375 8.59375 \r\nQ 29.6875 8.59375 32.8125 11.71875 \r\nQ 35.9375 14.84375 35.9375 21.484375 \r\nL 35.9375 68.75 \r\nL 44.921875 68.75 \r\nz\r\n\" id=\"SimHei-85\"/>\r\n       <path d=\"M 46.484375 45.3125 \r\nL 1.953125 45.3125 \r\nL 1.953125 51.5625 \r\nL 46.484375 51.5625 \r\nz\r\nM 46.484375 21.484375 \r\nL 1.953125 21.484375 \r\nL 1.953125 27.734375 \r\nL 46.484375 27.734375 \r\nz\r\n\" id=\"SimHei-61\"/>\r\n       <path d=\"M 13.28125 2.34375 \r\nQ 20.3125 32.03125 37.890625 61.328125 \r\nL 4.296875 61.328125 \r\nL 4.296875 68.359375 \r\nL 46.09375 68.359375 \r\nL 46.09375 61.71875 \r\nQ 27.734375 32.03125 21.875 2.34375 \r\nL 13.28125 2.34375 \r\nz\r\n\" id=\"SimHei-55\"/>\r\n       <path d=\"M 3.90625 19.140625 \r\nL 10.9375 20.3125 \r\nQ 12.5 15.234375 16.015625 11.90625 \r\nQ 19.53125 8.59375 24.796875 8.78125 \r\nQ 30.078125 8.984375 33.203125 13.078125 \r\nQ 36.328125 17.1875 35.9375 22.453125 \r\nQ 35.546875 27.734375 31.828125 30.65625 \r\nQ 28.125 33.59375 19.921875 34.765625 \r\nL 19.921875 39.84375 \r\nQ 28.125 40.625 31.828125 44.140625 \r\nQ 35.546875 47.65625 35.15625 53.3125 \r\nQ 34.765625 58.984375 30.078125 61.515625 \r\nQ 25.390625 64.0625 20.109375 62.109375 \r\nQ 14.84375 60.15625 11.71875 51.171875 \r\nL 4.6875 52.34375 \r\nQ 7.03125 59.375 11.125 64.0625 \r\nQ 15.234375 68.75 22.265625 69.53125 \r\nQ 29.296875 70.3125 34.5625 67.765625 \r\nQ 39.84375 65.234375 41.984375 59.953125 \r\nQ 44.140625 54.6875 42.578125 48.4375 \r\nQ 41.015625 42.1875 33.59375 37.5 \r\nQ 39.0625 35.15625 41.984375 30.46875 \r\nQ 44.921875 25.78125 43.9375 18.15625 \r\nQ 42.96875 10.546875 37.109375 5.859375 \r\nQ 31.25 1.171875 23.828125 1.359375 \r\nQ 16.40625 1.5625 10.9375 6.046875 \r\nQ 5.46875 10.546875 3.90625 19.140625 \r\nz\r\n\" id=\"SimHei-51\"/>\r\n       <path d=\"M 8.59375 20.703125 \r\nQ 11.328125 10.15625 17.96875 8.984375 \r\nQ 24.609375 7.8125 28.703125 10.34375 \r\nQ 32.8125 12.890625 34.5625 16.984375 \r\nQ 36.328125 21.09375 36.125 26.171875 \r\nQ 35.9375 31.25 33.390625 34.765625 \r\nQ 30.859375 38.28125 26.953125 39.453125 \r\nQ 23.046875 40.625 18.15625 39.453125 \r\nQ 13.28125 38.28125 10.15625 33.984375 \r\nL 3.515625 34.765625 \r\nQ 4.296875 37.109375 10.9375 68.359375 \r\nL 41.796875 68.359375 \r\nL 41.796875 61.328125 \r\nL 16.796875 61.328125 \r\nQ 14.84375 50.78125 12.890625 44.53125 \r\nQ 18.75 47.265625 23.828125 47.0625 \r\nQ 28.90625 46.875 33.59375 44.71875 \r\nQ 38.28125 42.578125 40.421875 38.859375 \r\nQ 42.578125 35.15625 43.546875 31.4375 \r\nQ 44.53125 27.734375 44.328125 23.4375 \r\nQ 44.140625 19.140625 42.578125 14.640625 \r\nQ 41.015625 10.15625 37.890625 7.21875 \r\nQ 34.765625 4.296875 30.265625 2.53125 \r\nQ 25.78125 0.78125 19.921875 1.171875 \r\nQ 14.0625 1.5625 8.78125 5.46875 \r\nQ 3.515625 9.375 1.5625 18.75 \r\nz\r\n\" id=\"SimHei-53\"/>\r\n      </defs>\r\n      <use xlink:href=\"#SimHei-86\"/>\r\n      <use x=\"50\" xlink:href=\"#SimHei-97\"/>\r\n      <use x=\"100\" xlink:href=\"#SimHei-108\"/>\r\n      <use x=\"150\" xlink:href=\"#SimHei-32\"/>\r\n      <use x=\"200\" xlink:href=\"#SimHei-65\"/>\r\n      <use x=\"250\" xlink:href=\"#SimHei-85\"/>\r\n      <use x=\"300\" xlink:href=\"#SimHei-67\"/>\r\n      <use x=\"350\" xlink:href=\"#SimHei-32\"/>\r\n      <use x=\"400\" xlink:href=\"#SimHei-61\"/>\r\n      <use x=\"450\" xlink:href=\"#SimHei-32\"/>\r\n      <use x=\"500\" xlink:href=\"#SimHei-48\"/>\r\n      <use x=\"550\" xlink:href=\"#SimHei-46\"/>\r\n      <use x=\"600\" xlink:href=\"#SimHei-55\"/>\r\n      <use x=\"650\" xlink:href=\"#SimHei-51\"/>\r\n      <use x=\"700\" xlink:href=\"#SimHei-49\"/>\r\n      <use x=\"750\" xlink:href=\"#SimHei-53\"/>\r\n     </g>\r\n    </g>\r\n   </g>\r\n  </g>\r\n </g>\r\n <defs>\r\n  <clipPath id=\"pd79d4fe22e\">\r\n   <rect height=\"434.88\" width=\"446.4\" x=\"46.95\" y=\"21.45\"/>\r\n  </clipPath>\r\n </defs>\r\n</svg>\r\n",
      "image/png": "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\n"
     },
     "metadata": {}
    }
   ],
   "source": [
    "from sklearn import metrics\n",
    "from sklearn.metrics import roc_auc_score\n",
    "\n",
    "\"\"\"预测并计算roc的相关指标\"\"\"\n",
    "val_pre_lgb = model.predict(X_val, num_iteration=model.best_iteration)\n",
    "fpr, tpr, threshold = metrics.roc_curve(y_val, val_pre_lgb)\n",
    "roc_auc = metrics.auc(fpr, tpr)\n",
    "print('未调参前lightgbm单模型在验证集上的AUC：{}'.format(roc_auc))\n",
    "\"\"\"画出roc曲线图\"\"\"\n",
    "plt.figure(figsize=(8, 8))\n",
    "plt.title('Validation ROC')\n",
    "plt.plot(fpr, tpr, 'b', label = 'Val AUC = %0.4f' % roc_auc)\n",
    "plt.ylim(0,1)\n",
    "plt.xlim(0,1)\n",
    "plt.legend(loc='best')\n",
    "plt.title('ROC')\n",
    "plt.ylabel('True Positive Rate')\n",
    "plt.xlabel('False Positive Rate')\n",
    "# 画出对角线\n",
    "plt.plot([0,1],[0,1],'r--')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "uuid": "2a94eb22-11f8-4069-a05e-5da4e9c061bc",
    "tags": []
   },
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": "************************************ 1 ************************************\n[LightGBM] [Warning] Unknown parameter: silent\nTraining until validation scores don't improve for 200 rounds\nEarly stopping, best iteration is:\n[357]\tvalid_0's auc: 0.729769\n[0.7297694322483247]\n************************************ 2 ************************************\n[LightGBM] [Warning] Unknown parameter: silent\nTraining until validation scores don't improve for 200 rounds\nEarly stopping, best iteration is:\n[391]\tvalid_0's auc: 0.731187\n[0.7297694322483247, 0.7311872828624951]\n************************************ 3 ************************************\n[LightGBM] [Warning] Unknown parameter: silent\nTraining until validation scores don't improve for 200 rounds\nEarly stopping, best iteration is:\n[465]\tvalid_0's auc: 0.732667\n[0.7297694322483247, 0.7311872828624951, 0.7326669254659628]\n************************************ 4 ************************************\n[LightGBM] [Warning] Unknown parameter: silent\nTraining until validation scores don't improve for 200 rounds\nEarly stopping, best iteration is:\n[497]\tvalid_0's auc: 0.727243\n[0.7297694322483247, 0.7311872828624951, 0.7326669254659628, 0.7272429362948426]\n************************************ 5 ************************************\n[LightGBM] [Warning] Unknown parameter: silent\nTraining until validation scores don't improve for 200 rounds\nEarly stopping, best iteration is:\n[361]\tvalid_0's auc: 0.732511\n[0.7297694322483247, 0.7311872828624951, 0.7326669254659628, 0.7272429362948426, 0.7325106201999415]\nlgb_scotrainre_list:[0.7297694322483247, 0.7311872828624951, 0.7326669254659628, 0.7272429362948426, 0.7325106201999415]\nlgb_score_mean:0.7306754394143133\nlgb_score_std:0.002009916196029024\n"
    }
   ],
   "source": [
    "import lightgbm as lgb\n",
    "\"\"\"使用lightgbm 5折交叉验证进行建模预测\"\"\"\n",
    "cv_scores = []\n",
    "for i, (train_index, valid_index) in enumerate(kf.split(X_train, y_train)):\n",
    "    print('************************************ {} ************************************'.format(str(i+1)))\n",
    "    X_train_split, y_train_split, X_val, y_val = X_train.iloc[train_index], y_train[train_index], X_train.iloc[valid_index], y_train[valid_index]\n",
    "    \n",
    "    train_matrix = lgb.Dataset(X_train_split, label=y_train_split)\n",
    "    valid_matrix = lgb.Dataset(X_val, label=y_val)\n",
    "\n",
    "    params = {\n",
    "                'boosting_type': 'gbdt',\n",
    "                'objective': 'binary',\n",
    "                'learning_rate': 0.1,\n",
    "                'metric': 'auc',\n",
    "        \n",
    "                'min_child_weight': 1e-3,\n",
    "                'num_leaves': 31,\n",
    "                'max_depth': -1,\n",
    "                'reg_lambda': 0,\n",
    "                'reg_alpha': 0,\n",
    "                'feature_fraction': 1,\n",
    "                'bagging_fraction': 1,\n",
    "                'bagging_freq': 0,\n",
    "                'seed': 2020,\n",
    "                'nthread': 8,\n",
    "                'silent': True,\n",
    "                'verbose': -1,\n",
    "    }\n",
    "    \n",
    "    model = lgb.train(params, train_set=train_matrix, num_boost_round=20000, valid_sets=valid_matrix, verbose_eval=1000, early_stopping_rounds=200)\n",
    "    val_pred = model.predict(X_val, num_iteration=model.best_iteration)\n",
    "    \n",
    "    cv_scores.append(roc_auc_score(y_val, val_pred))\n",
    "    print(cv_scores)\n",
    "\n",
    "print(\"lgb_scotrainre_list:{}\".format(cv_scores))\n",
    "print(\"lgb_score_mean:{}\".format(np.mean(cv_scores)))\n",
    "print(\"lgb_score_std:{}\".format(np.std(cv_scores)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "uuid": "ed8e1a87-46f7-4539-8c78-150275a6e94a"
   },
   "outputs": [],
   "source": [
    "from sklearn.model_selection import cross_val_score\n",
    "\n",
    "# 调objective\n",
    "best_obj = dict()\n",
    "for obj in objective:\n",
    "    model = LGBMRegressor(objective=obj)\n",
    "    \"\"\"预测并计算roc的相关指标\"\"\"\n",
    "    score = cross_val_score(model, X_train, y_train, cv=5, scoring='roc_auc').mean()\n",
    "    best_obj[obj] = score\n",
    "    \n",
    "# num_leaves\n",
    "best_leaves = dict()\n",
    "for leaves in num_leaves:\n",
    "    model = LGBMRegressor(objective=min(best_obj.items(), key=lambda x:x[1])[0], num_leaves=leaves)\n",
    "    \"\"\"预测并计算roc的相关指标\"\"\"\n",
    "    score = cross_val_score(model, X_train, y_train, cv=5, scoring='roc_auc').mean()\n",
    "    best_leaves[leaves] = score\n",
    "    \n",
    "# max_depth\n",
    "best_depth = dict()\n",
    "for depth in max_depth:\n",
    "    model = LGBMRegressor(objective=min(best_obj.items(), key=lambda x:x[1])[0],\n",
    "                          num_leaves=min(best_leaves.items(), key=lambda x:x[1])[0],\n",
    "                          max_depth=depth)\n",
    "    \"\"\"预测并计算roc的相关指标\"\"\"\n",
    "    score = cross_val_score(model, X_train, y_train, cv=5, scoring='roc_auc').mean()\n",
    "    best_depth[depth] = score\n",
    "\n",
    "\"\"\"\n",
    "可依次将模型的参数通过上面的方式进行调整优化，并且通过可视化观察在每一个最优参数下模型的得分情况\n",
    "\"\"\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "\"\"\"通过网格搜索确定最优参数\"\"\"\n",
    "from sklearn.model_selection import GridSearchCV\n",
    "\n",
    "def get_best_cv_params(learning_rate=0.1, n_estimators=581, num_leaves=31, max_depth=-1, bagging_fraction=1.0, \n",
    "                       feature_fraction=1.0, bagging_freq=0, min_data_in_leaf=20, min_child_weight=0.001, \n",
    "                       min_split_gain=0, reg_lambda=0, reg_alpha=0, param_grid=None):\n",
    "    # 设置5折交叉验证\n",
    "    cv_fold = StratifiedKFold(n_splits=5, random_state=0, shuffle=True, )\n",
    "    \n",
    "    model_lgb = lgb.LGBMClassifier(learning_rate=learning_rate,\n",
    "                                   n_estimators=n_estimators,\n",
    "                                   num_leaves=num_leaves,\n",
    "                                   max_depth=max_depth,\n",
    "                                   bagging_fraction=bagging_fraction,\n",
    "                                   feature_fraction=feature_fraction,\n",
    "                                   bagging_freq=bagging_freq,\n",
    "                                   min_data_in_leaf=min_data_in_leaf,\n",
    "                                   min_child_weight=min_child_weight,\n",
    "                                   min_split_gain=min_split_gain,\n",
    "                                   reg_lambda=reg_lambda,\n",
    "                                   reg_alpha=reg_alpha,\n",
    "                                   n_jobs= 8\n",
    "                                  )\n",
    "    grid_search = GridSearchCV(estimator=model_lgb, \n",
    "                               cv=cv_fold,\n",
    "                               param_grid=param_grid,\n",
    "                               scoring='roc_auc'\n",
    "                              )\n",
    "    grid_search.fit(X_train, y_train)\n",
    "\n",
    "    print('模型当前最优参数为:{}'.format(grid_search.best_params_))\n",
    "    print('模型当前最优得分为:{}'.format(grid_search.best_score_))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.model_selection import cross_val_score\n",
    "\n",
    "\"\"\"定义优化函数\"\"\"\n",
    "def rf_cv_lgb(num_leaves, max_depth, bagging_fraction, feature_fraction, bagging_freq, min_data_in_leaf, \n",
    "              min_child_weight, min_split_gain, reg_lambda, reg_alpha):\n",
    "    # 建立模型\n",
    "    model_lgb = lgb.LGBMClassifier(boosting_type='gbdt', bjective='binary', metric='auc',\n",
    "                                   learning_rate=0.1, n_estimators=5000,\n",
    "                                   num_leaves=int(num_leaves), max_depth=int(max_depth), \n",
    "                                   bagging_fraction=round(bagging_fraction, 2), feature_fraction=round(feature_fraction, 2),\n",
    "                                   bagging_freq=int(bagging_freq), min_data_in_leaf=int(min_data_in_leaf),\n",
    "                                   min_child_weight=min_child_weight, min_split_gain=min_split_gain,\n",
    "                                   reg_lambda=reg_lambda, reg_alpha=reg_alpha,\n",
    "                                   n_jobs= 8\n",
    "                                  )\n",
    "    \n",
    "    val = cross_val_score(model_lgb, X_train_split, y_train_split, cv=5, scoring='roc_auc').mean()\n",
    "    \n",
    "    return val"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "pip install bayesian-optimization"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "tags": [
     "outputPrepend"
    ]
   },
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": "set=62, min_child_samples=20 will be ignored. Current value: min_data_in_leaf=62\n[LightGBM] [Warning] bagging_fraction is set=0.92, subsample=1.0 will be ignored. Current value: bagging_fraction=0.92\n[LightGBM] [Warning] bagging_freq is set=58, subsample_freq=0 will be ignored. Current value: bagging_freq=58\n[LightGBM] [Warning] Unknown parameter: bjective\n[LightGBM] [Warning] feature_fraction is set=0.5, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=0.5\n[LightGBM] [Warning] min_data_in_leaf is set=62, min_child_samples=20 will be ignored. Current value: min_data_in_leaf=62\n[LightGBM] [Warning] bagging_fraction is set=0.92, subsample=1.0 will be ignored. Current value: bagging_fraction=0.92\n[LightGBM] [Warning] bagging_freq is set=58, subsample_freq=0 will be ignored. Current value: bagging_freq=58\n[LightGBM] [Warning] Unknown parameter: bjective\n[LightGBM] [Warning] feature_fraction is set=0.5, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=0.5\n[LightGBM] [Warning] min_data_in_leaf is set=62, min_child_samples=20 will be ignored. Current value: min_data_in_leaf=62\n[LightGBM] [Warning] bagging_fraction is set=0.92, subsample=1.0 will be ignored. Current value: bagging_fraction=0.92\n[LightGBM] [Warning] bagging_freq is set=58, subsample_freq=0 will be ignored. Current value: bagging_freq=58\n[LightGBM] [Warning] Unknown parameter: bjective\n[LightGBM] [Warning] feature_fraction is set=0.5, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=0.5\n[LightGBM] [Warning] min_data_in_leaf is set=62, min_child_samples=20 will be ignored. Current value: min_data_in_leaf=62\n[LightGBM] [Warning] bagging_fraction is set=0.92, subsample=1.0 will be ignored. Current value: bagging_fraction=0.92\n[LightGBM] [Warning] bagging_freq is set=58, subsample_freq=0 will be ignored. Current value: bagging_freq=58\n[LightGBM] [Warning] Unknown parameter: bjective\n[LightGBM] [Warning] feature_fraction is set=0.5, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=0.5\n[LightGBM] [Warning] min_data_in_leaf is set=62, min_child_samples=20 will be ignored. Current value: min_data_in_leaf=62\n[LightGBM] [Warning] bagging_fraction is set=0.92, subsample=1.0 will be ignored. Current value: bagging_fraction=0.92\n[LightGBM] [Warning] bagging_freq is set=58, subsample_freq=0 will be ignored. Current value: bagging_freq=58\n| \u001b[95m 9       \u001b[0m | \u001b[95m 0.7295  \u001b[0m | \u001b[95m 0.9227  \u001b[0m | \u001b[95m 58.7    \u001b[0m | \u001b[95m 0.5019  \u001b[0m | \u001b[95m 13.3    \u001b[0m | \u001b[95m 1.308   \u001b[0m | \u001b[95m 62.94   \u001b[0m | \u001b[95m 0.476   \u001b[0m | \u001b[95m 179.0   \u001b[0m | \u001b[95m 9.196   \u001b[0m | \u001b[95m 1.821   \u001b[0m |\n[LightGBM] [Warning] Unknown parameter: bjective\n[LightGBM] [Warning] feature_fraction is set=0.6, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=0.6\n[LightGBM] [Warning] min_data_in_leaf is set=54, min_child_samples=20 will be ignored. Current value: min_data_in_leaf=54\n[LightGBM] [Warning] bagging_fraction is set=0.99, subsample=1.0 will be ignored. Current value: bagging_fraction=0.99\n[LightGBM] [Warning] bagging_freq is set=98, subsample_freq=0 will be ignored. Current value: bagging_freq=98\n[LightGBM] [Warning] Unknown parameter: bjective\n[LightGBM] [Warning] feature_fraction is set=0.6, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=0.6\n[LightGBM] [Warning] min_data_in_leaf is set=54, min_child_samples=20 will be ignored. Current value: min_data_in_leaf=54\n[LightGBM] [Warning] bagging_fraction is set=0.99, subsample=1.0 will be ignored. Current value: bagging_fraction=0.99\n[LightGBM] [Warning] bagging_freq is set=98, subsample_freq=0 will be ignored. Current value: bagging_freq=98\n[LightGBM] [Warning] Unknown parameter: bjective\n[LightGBM] [Warning] feature_fraction is set=0.6, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=0.6\n[LightGBM] [Warning] min_data_in_leaf is set=54, min_child_samples=20 will be ignored. Current value: min_data_in_leaf=54\n[LightGBM] [Warning] bagging_fraction is set=0.99, subsample=1.0 will be ignored. Current value: bagging_fraction=0.99\n[LightGBM] [Warning] bagging_freq is set=98, subsample_freq=0 will be ignored. Current value: bagging_freq=98\n[LightGBM] [Warning] Unknown parameter: bjective\n[LightGBM] [Warning] feature_fraction is set=0.6, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=0.6\n[LightGBM] [Warning] min_data_in_leaf is set=54, min_child_samples=20 will be ignored. Current value: min_data_in_leaf=54\n[LightGBM] [Warning] bagging_fraction is set=0.99, subsample=1.0 will be ignored. Current value: bagging_fraction=0.99\n[LightGBM] [Warning] bagging_freq is set=98, subsample_freq=0 will be ignored. Current value: bagging_freq=98\n[LightGBM] [Warning] Unknown parameter: bjective\n[LightGBM] [Warning] feature_fraction is set=0.6, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=0.6\n[LightGBM] [Warning] min_data_in_leaf is set=54, min_child_samples=20 will be ignored. Current value: min_data_in_leaf=54\n[LightGBM] [Warning] bagging_fraction is set=0.99, subsample=1.0 will be ignored. Current value: bagging_fraction=0.99\n[LightGBM] [Warning] bagging_freq is set=98, subsample_freq=0 will be ignored. Current value: bagging_freq=98\n| \u001b[0m 10      \u001b[0m | \u001b[0m 0.7269  \u001b[0m | \u001b[0m 0.9918  \u001b[0m | \u001b[0m 98.25   \u001b[0m | \u001b[0m 0.5988  \u001b[0m | \u001b[0m 12.18   \u001b[0m | \u001b[0m 1.834   \u001b[0m | \u001b[0m 54.13   \u001b[0m | \u001b[0m 0.383   \u001b[0m | \u001b[0m 183.8   \u001b[0m | \u001b[0m 1.843   \u001b[0m | \u001b[0m 2.441   \u001b[0m |\n[LightGBM] [Warning] Unknown parameter: bjective\n[LightGBM] [Warning] feature_fraction is set=0.62, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=0.62\n[LightGBM] [Warning] min_data_in_leaf is set=58, min_child_samples=20 will be ignored. Current value: min_data_in_leaf=58\n[LightGBM] [Warning] bagging_fraction is set=0.79, subsample=1.0 will be ignored. Current value: bagging_fraction=0.79\n[LightGBM] [Warning] bagging_freq is set=60, subsample_freq=0 will be ignored. Current value: bagging_freq=60\n[LightGBM] [Warning] Unknown parameter: bjective\n[LightGBM] [Warning] feature_fraction is set=0.62, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=0.62\n[LightGBM] [Warning] min_data_in_leaf is set=58, min_child_samples=20 will be ignored. Current value: min_data_in_leaf=58\n[LightGBM] [Warning] bagging_fraction is set=0.79, subsample=1.0 will be ignored. Current value: bagging_fraction=0.79\n[LightGBM] [Warning] bagging_freq is set=60, subsample_freq=0 will be ignored. Current value: bagging_freq=60\n[LightGBM] [Warning] Unknown parameter: bjective\n[LightGBM] [Warning] feature_fraction is set=0.62, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=0.62\n[LightGBM] [Warning] min_data_in_leaf is set=58, min_child_samples=20 will be ignored. Current value: min_data_in_leaf=58\n[LightGBM] [Warning] bagging_fraction is set=0.79, subsample=1.0 will be ignored. Current value: bagging_fraction=0.79\n[LightGBM] [Warning] bagging_freq is set=60, subsample_freq=0 will be ignored. Current value: bagging_freq=60\n[LightGBM] [Warning] Unknown parameter: bjective\n[LightGBM] [Warning] feature_fraction is set=0.62, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=0.62\n[LightGBM] [Warning] min_data_in_leaf is set=58, min_child_samples=20 will be ignored. Current value: min_data_in_leaf=58\n[LightGBM] [Warning] bagging_fraction is set=0.79, subsample=1.0 will be ignored. Current value: bagging_fraction=0.79\n[LightGBM] [Warning] bagging_freq is set=60, subsample_freq=0 will be ignored. Current value: bagging_freq=60\n[LightGBM] [Warning] Unknown parameter: bjective\n[LightGBM] [Warning] feature_fraction is set=0.62, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=0.62\n[LightGBM] [Warning] min_data_in_leaf is set=58, min_child_samples=20 will be ignored. Current value: min_data_in_leaf=58\n[LightGBM] [Warning] bagging_fraction is set=0.79, subsample=1.0 will be ignored. Current value: bagging_fraction=0.79\n[LightGBM] [Warning] bagging_freq is set=60, subsample_freq=0 will be ignored. Current value: bagging_freq=60\n| \u001b[0m 11      \u001b[0m | \u001b[0m 0.7293  \u001b[0m | \u001b[0m 0.7945  \u001b[0m | \u001b[0m 60.19   \u001b[0m | \u001b[0m 0.6216  \u001b[0m | \u001b[0m 14.39   \u001b[0m | \u001b[0m 2.068   \u001b[0m | \u001b[0m 58.32   \u001b[0m | \u001b[0m 0.8668  \u001b[0m | \u001b[0m 180.1   \u001b[0m | \u001b[0m 9.567   \u001b[0m | \u001b[0m 3.992   \u001b[0m |\n[LightGBM] [Warning] Unknown parameter: bjective\n[LightGBM] [Warning] feature_fraction is set=0.6, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=0.6\n[LightGBM] [Warning] min_data_in_leaf is set=98, min_child_samples=20 will be ignored. Current value: min_data_in_leaf=98\n[LightGBM] [Warning] bagging_fraction is set=0.52, subsample=1.0 will be ignored. Current value: bagging_fraction=0.52\n[LightGBM] [Warning] bagging_freq is set=19, subsample_freq=0 will be ignored. Current value: bagging_freq=19\n[LightGBM] [Warning] Unknown parameter: bjective\n[LightGBM] [Warning] feature_fraction is set=0.6, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=0.6\n[LightGBM] [Warning] min_data_in_leaf is set=98, min_child_samples=20 will be ignored. Current value: min_data_in_leaf=98\n[LightGBM] [Warning] bagging_fraction is set=0.52, subsample=1.0 will be ignored. Current value: bagging_fraction=0.52\n[LightGBM] [Warning] bagging_freq is set=19, subsample_freq=0 will be ignored. Current value: bagging_freq=19\n[LightGBM] [Warning] Unknown parameter: bjective\n[LightGBM] [Warning] feature_fraction is set=0.6, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=0.6\n[LightGBM] [Warning] min_data_in_leaf is set=98, min_child_samples=20 will be ignored. Current value: min_data_in_leaf=98\n[LightGBM] [Warning] bagging_fraction is set=0.52, subsample=1.0 will be ignored. Current value: bagging_fraction=0.52\n[LightGBM] [Warning] bagging_freq is set=19, subsample_freq=0 will be ignored. Current value: bagging_freq=19\n[LightGBM] [Warning] Unknown parameter: bjective\n[LightGBM] [Warning] feature_fraction is set=0.6, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=0.6\n[LightGBM] [Warning] min_data_in_leaf is set=98, min_child_samples=20 will be ignored. Current value: min_data_in_leaf=98\n[LightGBM] [Warning] bagging_fraction is set=0.52, subsample=1.0 will be ignored. Current value: bagging_fraction=0.52\n[LightGBM] [Warning] bagging_freq is set=19, subsample_freq=0 will be ignored. Current value: bagging_freq=19\n[LightGBM] [Warning] Unknown parameter: bjective\n[LightGBM] [Warning] feature_fraction is set=0.6, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=0.6\n[LightGBM] [Warning] min_data_in_leaf is set=98, min_child_samples=20 will be ignored. Current value: min_data_in_leaf=98\n[LightGBM] [Warning] bagging_fraction is set=0.52, subsample=1.0 will be ignored. Current value: bagging_fraction=0.52\n[LightGBM] [Warning] bagging_freq is set=19, subsample_freq=0 will be ignored. Current value: bagging_freq=19\n| \u001b[0m 12      \u001b[0m | \u001b[0m 0.7215  \u001b[0m | \u001b[0m 0.521   \u001b[0m | \u001b[0m 19.27   \u001b[0m | \u001b[0m 0.6     \u001b[0m | \u001b[0m 17.56   \u001b[0m | \u001b[0m 8.971   \u001b[0m | \u001b[0m 98.53   \u001b[0m | \u001b[0m 0.9352  \u001b[0m | \u001b[0m 181.6   \u001b[0m | \u001b[0m 3.499   \u001b[0m | \u001b[0m 4.415   \u001b[0m |\n[LightGBM] [Warning] Unknown parameter: bjective\n[LightGBM] [Warning] feature_fraction is set=1.0, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1.0\n[LightGBM] [Warning] min_data_in_leaf is set=90, min_child_samples=20 will be ignored. Current value: min_data_in_leaf=90\n[LightGBM] [Warning] bagging_fraction is set=1.0, subsample=1.0 will be ignored. Current value: bagging_fraction=1.0\n[LightGBM] [Warning] bagging_freq is set=82, subsample_freq=0 will be ignored. Current value: bagging_freq=82\n[LightGBM] [Warning] Unknown parameter: bjective\n[LightGBM] [Warning] feature_fraction is set=1.0, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1.0\n[LightGBM] [Warning] min_data_in_leaf is set=90, min_child_samples=20 will be ignored. Current value: min_data_in_leaf=90\n[LightGBM] [Warning] bagging_fraction is set=1.0, subsample=1.0 will be ignored. Current value: bagging_fraction=1.0\n[LightGBM] [Warning] bagging_freq is set=82, subsample_freq=0 will be ignored. Current value: bagging_freq=82\n[LightGBM] [Warning] Unknown parameter: bjective\n[LightGBM] [Warning] feature_fraction is set=1.0, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1.0\n[LightGBM] [Warning] min_data_in_leaf is set=90, min_child_samples=20 will be ignored. Current value: min_data_in_leaf=90\n[LightGBM] [Warning] bagging_fraction is set=1.0, subsample=1.0 will be ignored. Current value: bagging_fraction=1.0\n[LightGBM] [Warning] bagging_freq is set=82, subsample_freq=0 will be ignored. Current value: bagging_freq=82\n[LightGBM] [Warning] Unknown parameter: bjective\n[LightGBM] [Warning] feature_fraction is set=1.0, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1.0\n[LightGBM] [Warning] min_data_in_leaf is set=90, min_child_samples=20 will be ignored. Current value: min_data_in_leaf=90\n[LightGBM] [Warning] bagging_fraction is set=1.0, subsample=1.0 will be ignored. Current value: bagging_fraction=1.0\n[LightGBM] [Warning] bagging_freq is set=82, subsample_freq=0 will be ignored. Current value: bagging_freq=82\n[LightGBM] [Warning] Unknown parameter: bjective\n[LightGBM] [Warning] feature_fraction is set=1.0, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1.0\n[LightGBM] [Warning] min_data_in_leaf is set=90, min_child_samples=20 will be ignored. Current value: min_data_in_leaf=90\n[LightGBM] [Warning] bagging_fraction is set=1.0, subsample=1.0 will be ignored. Current value: bagging_fraction=1.0\n[LightGBM] [Warning] bagging_freq is set=82, subsample_freq=0 will be ignored. Current value: bagging_freq=82\n| \u001b[95m 13      \u001b[0m | \u001b[95m 0.7304  \u001b[0m | \u001b[95m 1.0     \u001b[0m | \u001b[95m 82.64   \u001b[0m | \u001b[95m 1.0     \u001b[0m | \u001b[95m 3.0     \u001b[0m | \u001b[95m 0.0     \u001b[0m | \u001b[95m 90.6    \u001b[0m | \u001b[95m 0.0     \u001b[0m | \u001b[95m 148.2   \u001b[0m | \u001b[95m 10.0    \u001b[0m | \u001b[95m 0.0     \u001b[0m |\n[LightGBM] [Warning] Unknown parameter: bjective\n[LightGBM] [Warning] feature_fraction is set=0.5, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=0.5\n[LightGBM] [Warning] min_data_in_leaf is set=100, min_child_samples=20 will be ignored. Current value: min_data_in_leaf=100\n[LightGBM] [Warning] bagging_fraction is set=1.0, subsample=1.0 will be ignored. Current value: bagging_fraction=1.0\n[LightGBM] [Warning] bagging_freq is set=100, subsample_freq=0 will be ignored. Current value: bagging_freq=100\n[LightGBM] [Warning] Unknown parameter: bjective\n[LightGBM] [Warning] feature_fraction is set=0.5, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=0.5\n[LightGBM] [Warning] min_data_in_leaf is set=100, min_child_samples=20 will be ignored. Current value: min_data_in_leaf=100\n[LightGBM] [Warning] bagging_fraction is set=1.0, subsample=1.0 will be ignored. Current value: bagging_fraction=1.0\n[LightGBM] [Warning] bagging_freq is set=100, subsample_freq=0 will be ignored. Current value: bagging_freq=100\n[LightGBM] [Warning] Unknown parameter: bjective\n[LightGBM] [Warning] feature_fraction is set=0.5, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=0.5\n[LightGBM] [Warning] min_data_in_leaf is set=100, min_child_samples=20 will be ignored. Current value: min_data_in_leaf=100\n[LightGBM] [Warning] bagging_fraction is set=1.0, subsample=1.0 will be ignored. Current value: bagging_fraction=1.0\n[LightGBM] [Warning] bagging_freq is set=100, subsample_freq=0 will be ignored. Current value: bagging_freq=100\n[LightGBM] [Warning] Unknown parameter: bjective\n[LightGBM] [Warning] feature_fraction is set=0.5, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=0.5\n[LightGBM] [Warning] min_data_in_leaf is set=100, min_child_samples=20 will be ignored. Current value: min_data_in_leaf=100\n[LightGBM] [Warning] bagging_fraction is set=1.0, subsample=1.0 will be ignored. Current value: bagging_fraction=1.0\n[LightGBM] [Warning] bagging_freq is set=100, subsample_freq=0 will be ignored. Current value: bagging_freq=100\n[LightGBM] [Warning] Unknown parameter: bjective\n[LightGBM] [Warning] feature_fraction is set=0.5, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=0.5\n[LightGBM] [Warning] min_data_in_leaf is set=100, min_child_samples=20 will be ignored. Current value: min_data_in_leaf=100\n[LightGBM] [Warning] bagging_fraction is set=1.0, subsample=1.0 will be ignored. Current value: bagging_fraction=1.0\n[LightGBM] [Warning] bagging_freq is set=100, subsample_freq=0 will be ignored. Current value: bagging_freq=100\n| \u001b[0m 14      \u001b[0m | \u001b[0m 0.7303  \u001b[0m | \u001b[0m 1.0     \u001b[0m | \u001b[0m 100.0   \u001b[0m | \u001b[0m 0.5     \u001b[0m | \u001b[0m 20.0    \u001b[0m | \u001b[0m 0.0     \u001b[0m | \u001b[0m 100.0   \u001b[0m | \u001b[0m 1.0     \u001b[0m | \u001b[0m 121.6   \u001b[0m | \u001b[0m 10.0    \u001b[0m | \u001b[0m 10.0    \u001b[0m |\n[LightGBM] [Warning] Unknown parameter: bjective\n[LightGBM] [Warning] feature_fraction is set=1.0, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1.0\n[LightGBM] [Warning] min_data_in_leaf is set=79, min_child_samples=20 will be ignored. Current value: min_data_in_leaf=79\n[LightGBM] [Warning] bagging_fraction is set=1.0, subsample=1.0 will be ignored. Current value: bagging_fraction=1.0\n[LightGBM] [Warning] bagging_freq is set=100, subsample_freq=0 will be ignored. Current value: bagging_freq=100\n[LightGBM] [Warning] Unknown parameter: bjective\n[LightGBM] [Warning] feature_fraction is set=1.0, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1.0\n[LightGBM] [Warning] min_data_in_leaf is set=79, min_child_samples=20 will be ignored. Current value: min_data_in_leaf=79\n[LightGBM] [Warning] bagging_fraction is set=1.0, subsample=1.0 will be ignored. Current value: bagging_fraction=1.0\n[LightGBM] [Warning] bagging_freq is set=100, subsample_freq=0 will be ignored. Current value: bagging_freq=100\n[LightGBM] [Warning] Unknown parameter: bjective\n[LightGBM] [Warning] feature_fraction is set=1.0, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1.0\n[LightGBM] [Warning] min_data_in_leaf is set=79, min_child_samples=20 will be ignored. Current value: min_data_in_leaf=79\n[LightGBM] [Warning] bagging_fraction is set=1.0, subsample=1.0 will be ignored. Current value: bagging_fraction=1.0\n[LightGBM] [Warning] bagging_freq is set=100, subsample_freq=0 will be ignored. Current value: bagging_freq=100\n[LightGBM] [Warning] Unknown parameter: bjective\n[LightGBM] [Warning] feature_fraction is set=1.0, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1.0\n[LightGBM] [Warning] min_data_in_leaf is set=79, min_child_samples=20 will be ignored. Current value: min_data_in_leaf=79\n[LightGBM] [Warning] bagging_fraction is set=1.0, subsample=1.0 will be ignored. Current value: bagging_fraction=1.0\n[LightGBM] [Warning] bagging_freq is set=100, subsample_freq=0 will be ignored. Current value: bagging_freq=100\n[LightGBM] [Warning] Unknown parameter: bjective\n[LightGBM] [Warning] feature_fraction is set=1.0, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1.0\n[LightGBM] [Warning] min_data_in_leaf is set=79, min_child_samples=20 will be ignored. Current value: min_data_in_leaf=79\n[LightGBM] [Warning] bagging_fraction is set=1.0, subsample=1.0 will be ignored. Current value: bagging_fraction=1.0\n[LightGBM] [Warning] bagging_freq is set=100, subsample_freq=0 will be ignored. Current value: bagging_freq=100\n| \u001b[0m 15      \u001b[0m | \u001b[0m 0.7034  \u001b[0m | \u001b[0m 1.0     \u001b[0m | \u001b[0m 100.0   \u001b[0m | \u001b[0m 1.0     \u001b[0m | \u001b[0m 20.0    \u001b[0m | \u001b[0m 10.0    \u001b[0m | \u001b[0m 79.64   \u001b[0m | \u001b[0m 0.0     \u001b[0m | \u001b[0m 151.7   \u001b[0m | \u001b[0m 10.0    \u001b[0m | \u001b[0m 0.0     \u001b[0m |\n=================================================================================================================================================\n"
    }
   ],
   "source": [
    "from bayes_opt import BayesianOptimization\n",
    "\"\"\"定义优化参数\"\"\"\n",
    "bayes_lgb = BayesianOptimization(\n",
    "    rf_cv_lgb, \n",
    "    {\n",
    "        'num_leaves':(10, 200),\n",
    "        'max_depth':(3, 20),\n",
    "        'bagging_fraction':(0.5, 1.0),\n",
    "        'feature_fraction':(0.5, 1.0),\n",
    "        'bagging_freq':(0, 100),\n",
    "        'min_data_in_leaf':(10,100),\n",
    "        'min_child_weight':(0, 10),\n",
    "        'min_split_gain':(0.0, 1.0),\n",
    "        'reg_alpha':(0.0, 10),\n",
    "        'reg_lambda':(0.0, 10),\n",
    "    }\n",
    ")\n",
    "\n",
    "\"\"\"开始优化\"\"\"\n",
    "bayes_lgb.maximize(n_iter=10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": "{'target': 0.7303742518283423,\n 'params': {'bagging_fraction': 1.0,\n  'bagging_freq': 82.64445661897811,\n  'feature_fraction': 1.0,\n  'max_depth': 3.0,\n  'min_child_weight': 0.0,\n  'min_data_in_leaf': 90.60488051729797,\n  'min_split_gain': 0.0,\n  'num_leaves': 148.18881280538147,\n  'reg_alpha': 10.0,\n  'reg_lambda': 0.0}}"
     },
     "metadata": {},
     "execution_count": 10
    }
   ],
   "source": [
    "\"\"\"显示优化结果\"\"\"\n",
    "bayes_lgb.max"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": "[LightGBM] [Warning] Unknown parameter: silent\n迭代次数10389\n最终模型的AUC为0.732178961274865\n"
    }
   ],
   "source": [
    "\"\"\"调整一个较小的学习率，并通过cv函数确定当前最优的迭代次数\"\"\"\n",
    "base_params_lgb = {\n",
    "                    'boosting_type': 'gbdt',\n",
    "                    'objective': 'binary',\n",
    "                    'metric': 'auc',\n",
    "                    'learning_rate': 0.01,\n",
    "                    'num_leaves': 14,\n",
    "                    'max_depth': 19,\n",
    "                    'min_data_in_leaf': 37,\n",
    "                    'min_child_weight':1.6,\n",
    "                    'bagging_fraction': 0.98,\n",
    "                    'feature_fraction': 0.69,\n",
    "                    'bagging_freq': 96,\n",
    "                    'reg_lambda': 9,\n",
    "                    'reg_alpha': 7,\n",
    "                    'min_split_gain': 0.4,\n",
    "                    'nthread': 8,\n",
    "                    'seed': 2020,\n",
    "                    'silent': True,\n",
    "                    'verbose': -1,\n",
    "}\n",
    "\n",
    "cv_result_lgb = lgb.cv(\n",
    "    train_set=train_matrix,\n",
    "    early_stopping_rounds=1000, \n",
    "    num_boost_round=20000,\n",
    "    nfold=5,\n",
    "    stratified=True,\n",
    "    shuffle=True,\n",
    "    params=base_params_lgb,\n",
    "    metrics='auc',\n",
    "    seed=0\n",
    ")\n",
    "\n",
    "print('迭代次数{}'.format(len(cv_result_lgb['auc-mean'])))\n",
    "print('最终模型的AUC为{}'.format(max(cv_result_lgb['auc-mean'])))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": "************************************ 1 ************************************\n[LightGBM] [Warning] Unknown parameter: silent\n[LightGBM] [Info] Number of positive: 95372, number of negative: 394821\n[LightGBM] [Warning] Auto-choosing col-wise multi-threading, the overhead of testing was 0.110254 seconds.\nYou can set `force_col_wise=true` to remove the overhead.\n[LightGBM] [Info] Total Bins 3230\n[LightGBM] [Info] Number of data points in the train set: 490193, number of used features: 41\n[LightGBM] [Warning] Unknown parameter: silent\n[LightGBM] [Info] [binary:BoostFromScore]: pavg=0.194560 -> initscore=-1.420647\n[LightGBM] [Info] Start training from score -1.420647\nTraining until validation scores don't improve for 200 rounds\n[1000]\tvalid_0's auc: 0.725226\n[2000]\tvalid_0's auc: 0.728781\n[3000]\tvalid_0's auc: 0.729981\n[4000]\tvalid_0's auc: 0.730752\n[5000]\tvalid_0's auc: 0.731214\n[6000]\tvalid_0's auc: 0.731547\n[7000]\tvalid_0's auc: 0.731824\n[8000]\tvalid_0's auc: 0.732016\n[9000]\tvalid_0's auc: 0.732198\n[10000]\tvalid_0's auc: 0.732366\nEarly stopping, best iteration is:\n[9945]\tvalid_0's auc: 0.732371\n[0.7323709874302734]\n************************************ 2 ************************************\n[LightGBM] [Warning] Unknown parameter: silent\n[LightGBM] [Warning] Unknown parameter: silent\n[LightGBM] [Info] Number of positive: 95585, number of negative: 394608\n[LightGBM] [Warning] Auto-choosing col-wise multi-threading, the overhead of testing was 0.148456 seconds.\nYou can set `force_col_wise=true` to remove the overhead.\n[LightGBM] [Info] Total Bins 3231\n[LightGBM] [Info] Number of data points in the train set: 490193, number of used features: 41\n[LightGBM] [Warning] Unknown parameter: silent\n[LightGBM] [Info] [binary:BoostFromScore]: pavg=0.194995 -> initscore=-1.417877\n[LightGBM] [Info] Start training from score -1.417877\nTraining until validation scores don't improve for 200 rounds\n[1000]\tvalid_0's auc: 0.727252\n[2000]\tvalid_0's auc: 0.730361\n[3000]\tvalid_0's auc: 0.731559\n[4000]\tvalid_0's auc: 0.732304\n[5000]\tvalid_0's auc: 0.732721\n[6000]\tvalid_0's auc: 0.733067\n[7000]\tvalid_0's auc: 0.733332\n[8000]\tvalid_0's auc: 0.733505\n[9000]\tvalid_0's auc: 0.733665\nEarly stopping, best iteration is:\n[9212]\tvalid_0's auc: 0.733766\n[0.7323709874302734, 0.7337663030205843]\n************************************ 3 ************************************\n[LightGBM] [Warning] Unknown parameter: silent\n[LightGBM] [Warning] Unknown parameter: silent\n[LightGBM] [Info] Number of positive: 95808, number of negative: 394386\n[LightGBM] [Warning] Auto-choosing col-wise multi-threading, the overhead of testing was 0.127915 seconds.\nYou can set `force_col_wise=true` to remove the overhead.\n[LightGBM] [Info] Total Bins 3230\n[LightGBM] [Info] Number of data points in the train set: 490194, number of used features: 41\n[LightGBM] [Warning] Unknown parameter: silent\n[LightGBM] [Info] [binary:BoostFromScore]: pavg=0.195449 -> initscore=-1.414984\n[LightGBM] [Info] Start training from score -1.414984\nTraining until validation scores don't improve for 200 rounds\n[1000]\tvalid_0's auc: 0.727254\n[2000]\tvalid_0's auc: 0.731083\n[3000]\tvalid_0's auc: 0.732438\n[4000]\tvalid_0's auc: 0.733359\n[5000]\tvalid_0's auc: 0.734007\n[6000]\tvalid_0's auc: 0.734488\n[7000]\tvalid_0's auc: 0.734972\n[8000]\tvalid_0's auc: 0.735272\n[9000]\tvalid_0's auc: 0.735555\n[10000]\tvalid_0's auc: 0.735717\n[11000]\tvalid_0's auc: 0.73583\nEarly stopping, best iteration is:\n[11096]\tvalid_0's auc: 0.735843\n[0.7323709874302734, 0.7337663030205843, 0.735843287813751]\n************************************ 4 ************************************\n[LightGBM] [Warning] Unknown parameter: silent\n[LightGBM] [Warning] Unknown parameter: silent\n[LightGBM] [Info] Number of positive: 95714, number of negative: 394480\n[LightGBM] [Warning] Auto-choosing col-wise multi-threading, the overhead of testing was 0.115353 seconds.\nYou can set `force_col_wise=true` to remove the overhead.\n[LightGBM] [Info] Total Bins 3232\n[LightGBM] [Info] Number of data points in the train set: 490194, number of used features: 41\n[LightGBM] [Warning] Unknown parameter: silent\n[LightGBM] [Info] [binary:BoostFromScore]: pavg=0.195257 -> initscore=-1.416204\n[LightGBM] [Info] Start training from score -1.416204\nTraining until validation scores don't improve for 200 rounds\n[1000]\tvalid_0's auc: 0.723602\n[2000]\tvalid_0's auc: 0.727002\n[3000]\tvalid_0's auc: 0.728152\n[4000]\tvalid_0's auc: 0.728783\n[5000]\tvalid_0's auc: 0.729372\n[6000]\tvalid_0's auc: 0.729672\n[7000]\tvalid_0's auc: 0.729987\n[8000]\tvalid_0's auc: 0.730224\n[9000]\tvalid_0's auc: 0.730417\nEarly stopping, best iteration is:\n[9406]\tvalid_0's auc: 0.730497\n[0.7323709874302734, 0.7337663030205843, 0.735843287813751, 0.7304969494658524]\n************************************ 5 ************************************\n[LightGBM] [Warning] Unknown parameter: silent\n[LightGBM] [Warning] Unknown parameter: silent\n[LightGBM] [Info] Number of positive: 95685, number of negative: 394509\n[LightGBM] [Warning] Auto-choosing col-wise multi-threading, the overhead of testing was 0.118400 seconds.\nYou can set `force_col_wise=true` to remove the overhead.\n[LightGBM] [Info] Total Bins 3228\n[LightGBM] [Info] Number of data points in the train set: 490194, number of used features: 41\n[LightGBM] [Warning] Unknown parameter: silent\n[LightGBM] [Info] [binary:BoostFromScore]: pavg=0.195198 -> initscore=-1.416580\n[LightGBM] [Info] Start training from score -1.416580\nTraining until validation scores don't improve for 200 rounds\n[1000]\tvalid_0's auc: 0.72832\n[2000]\tvalid_0's auc: 0.731827\n[3000]\tvalid_0's auc: 0.732971\n[4000]\tvalid_0's auc: 0.733723\n[5000]\tvalid_0's auc: 0.734284\n[6000]\tvalid_0's auc: 0.734621\n[7000]\tvalid_0's auc: 0.734958\nEarly stopping, best iteration is:\n[7391]\tvalid_0's auc: 0.735086\n[0.7323709874302734, 0.7337663030205843, 0.735843287813751, 0.7304969494658524, 0.7350859576085513]\nlgb_scotrainre_list:[0.7323709874302734, 0.7337663030205843, 0.735843287813751, 0.7304969494658524, 0.7350859576085513]\nlgb_score_mean:0.7335126970678025\nlgb_score_std:0.001916734328411677\n"
    }
   ],
   "source": [
    "import lightgbm as lgb\n",
    "\"\"\"使用lightgbm 5折交叉验证进行建模预测\"\"\"\n",
    "cv_scores = []\n",
    "for i, (train_index, valid_index) in enumerate(kf.split(X_train, y_train)):\n",
    "    print('************************************ {} ************************************'.format(str(i+1)))\n",
    "    X_train_split, y_train_split, X_val, y_val = X_train.iloc[train_index], y_train[train_index], X_train.iloc[valid_index], y_train[valid_index]\n",
    "    \n",
    "    train_matrix = lgb.Dataset(X_train_split, label=y_train_split)\n",
    "    valid_matrix = lgb.Dataset(X_val, label=y_val)\n",
    "\n",
    "    params = {\n",
    "                'boosting_type': 'gbdt',\n",
    "                'objective': 'binary',\n",
    "                'metric': 'auc',\n",
    "                'learning_rate': 0.01,\n",
    "                'num_leaves': 14,\n",
    "                'max_depth': 19,\n",
    "                'min_data_in_leaf': 37,\n",
    "                'min_child_weight':1.6,\n",
    "                'bagging_fraction': 0.98,\n",
    "                'feature_fraction': 0.69,\n",
    "                'bagging_freq': 96,\n",
    "                'reg_lambda': 9,\n",
    "                'reg_alpha': 7,\n",
    "                'min_split_gain': 0.4,\n",
    "                'nthread': 8,\n",
    "                'seed': 2020,\n",
    "                'silent': True,\n",
    "    }\n",
    "    \n",
    "    model = lgb.train(params, train_set=train_matrix, num_boost_round=14269, valid_sets=valid_matrix, verbose_eval=1000, early_stopping_rounds=200)\n",
    "    val_pred = model.predict(X_val, num_iteration=model.best_iteration)\n",
    "    \n",
    "    cv_scores.append(roc_auc_score(y_val, val_pred))\n",
    "    print(cv_scores)\n",
    "\n",
    "print(\"lgb_scotrainre_list:{}\".format(cv_scores))\n",
    "print(\"lgb_score_mean:{}\".format(np.mean(cv_scores)))\n",
    "print(\"lgb_score_std:{}\".format(np.std(cv_scores)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": "[LightGBM] [Warning] Unknown parameter: silent\n[LightGBM] [Warning] Unknown parameter: silent\n[LightGBM] [Warning] Unknown parameter: silent\n[LightGBM] [Warning] Unknown parameter: silent\n[LightGBM] [Warning] Unknown parameter: silent\n[LightGBM] [Info] Number of positive: 95685, number of negative: 394509\n[LightGBM] [Warning] Auto-choosing col-wise multi-threading, the overhead of testing was 0.135311 seconds.\nYou can set `force_col_wise=true` to remove the overhead.\n[LightGBM] [Info] Total Bins 3228\n[LightGBM] [Info] Number of data points in the train set: 490194, number of used features: 41\n[LightGBM] [Info] [binary:BoostFromScore]: pavg=0.195198 -> initscore=-1.416580\n[LightGBM] [Info] Start training from score -1.416580\nTraining until validation scores don't improve for 200 rounds\n[1000]\tvalid_0's auc: 0.72832\n[2000]\tvalid_0's auc: 0.731827\n[3000]\tvalid_0's auc: 0.732971\n[4000]\tvalid_0's auc: 0.733723\n[5000]\tvalid_0's auc: 0.734284\n[6000]\tvalid_0's auc: 0.734621\n[7000]\tvalid_0's auc: 0.734958\nEarly stopping, best iteration is:\n[7391]\tvalid_0's auc: 0.735086\n调参后lightgbm单模型在验证集上的AUC：0.7350859576085513\n"
    },
    {
     "output_type": "display_data",
     "data": {
      "text/plain": "<Figure size 576x576 with 1 Axes>",
      "image/svg+xml": "<?xml version=\"1.0\" encoding=\"utf-8\" standalone=\"no\"?>\r\n<!DOCTYPE svg PUBLIC \"-//W3C//DTD SVG 1.1//EN\"\r\n  \"http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd\">\r\n<!-- Created with matplotlib (https://matplotlib.org/) -->\r\n<svg height=\"495.7175pt\" version=\"1.1\" viewBox=\"0 0 508.8 495.7175\" width=\"508.8pt\" xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\">\r\n <metadata>\r\n  <rdf:RDF xmlns:cc=\"http://creativecommons.org/ns#\" xmlns:dc=\"http://purl.org/dc/elements/1.1/\" xmlns:rdf=\"http://www.w3.org/1999/02/22-rdf-syntax-ns#\">\r\n   <cc:Work>\r\n    <dc:type rdf:resource=\"http://purl.org/dc/dcmitype/StillImage\"/>\r\n    <dc:date>2020-09-25T16:36:14.648694</dc:date>\r\n    <dc:format>image/svg+xml</dc:format>\r\n    <dc:creator>\r\n     <cc:Agent>\r\n      <dc:title>Matplotlib v3.3.1, https://matplotlib.org/</dc:title>\r\n     </cc:Agent>\r\n    </dc:creator>\r\n   </cc:Work>\r\n  </rdf:RDF>\r\n </metadata>\r\n <defs>\r\n  <style type=\"text/css\">*{stroke-linecap:butt;stroke-linejoin:round;}</style>\r\n </defs>\r\n <g id=\"figure_1\">\r\n  <g id=\"patch_1\">\r\n   <path d=\"M 0 495.7175 \r\nL 508.8 495.7175 \r\nL 508.8 0 \r\nL 0 0 \r\nz\r\n\" style=\"fill:#ffffff;\"/>\r\n  </g>\r\n  <g id=\"axes_1\">\r\n   <g id=\"patch_2\">\r\n    <path d=\"M 46.95 456.33 \r\nL 493.35 456.33 \r\nL 493.35 21.45 \r\nL 46.95 21.45 \r\nz\r\n\" style=\"fill:#eaeaf2;\"/>\r\n   </g>\r\n   <g id=\"matplotlib.axis_1\">\r\n    <g id=\"xtick_1\">\r\n     <g id=\"line2d_1\">\r\n      <path clip-path=\"url(#pbe2946be89)\" d=\"M 46.95 456.33 \r\nL 46.95 21.45 \r\n\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;\"/>\r\n     </g>\r\n     <g id=\"text_1\">\r\n      <!-- 0.0 -->\r\n      <g style=\"fill:#262626;\" transform=\"translate(38.7 473.3925)scale(0.11 -0.11)\">\r\n       <defs>\r\n        <path d=\"M 3.125 29.296875 \r\nQ 3.90625 50 6.4375 56.046875 \r\nQ 8.984375 62.109375 13.671875 66.015625 \r\nQ 18.359375 69.921875 25.1875 69.921875 \r\nQ 32.03125 69.921875 37.109375 64.25 \r\nQ 42.1875 58.59375 43.75 50 \r\nQ 45.3125 41.40625 44.71875 30.265625 \r\nQ 44.140625 19.140625 40.8125 12.109375 \r\nQ 37.5 5.078125 30.859375 2.34375 \r\nQ 24.21875 -0.390625 17.578125 2.921875 \r\nQ 10.9375 6.25 8.203125 11.71875 \r\nQ 5.46875 17.1875 4.296875 23.234375 \r\nQ 3.125 29.296875 3.90625 50 \r\nz\r\nM 12.890625 52.734375 \r\nQ 10.546875 31.25 12.5 22.84375 \r\nQ 14.453125 14.453125 18.9375 10.9375 \r\nQ 23.4375 7.421875 28.125 9.5625 \r\nQ 32.8125 11.71875 34.953125 18.15625 \r\nQ 37.109375 24.609375 37.109375 32.21875 \r\nQ 37.109375 39.84375 36.515625 46.09375 \r\nQ 35.9375 52.34375 33 57.421875 \r\nQ 30.078125 62.5 25.1875 62.6875 \r\nQ 20.3125 62.890625 16.59375 57.8125 \r\nQ 12.890625 52.734375 10.546875 31.25 \r\nz\r\n\" id=\"SimHei-48\"/>\r\n        <path d=\"M 16.796875 1.953125 \r\nL 7.8125 1.953125 \r\nL 7.8125 10.546875 \r\nL 16.796875 10.546875 \r\nz\r\n\" id=\"SimHei-46\"/>\r\n       </defs>\r\n       <use xlink:href=\"#SimHei-48\"/>\r\n       <use x=\"50\" xlink:href=\"#SimHei-46\"/>\r\n       <use x=\"100\" xlink:href=\"#SimHei-48\"/>\r\n      </g>\r\n     </g>\r\n    </g>\r\n    <g id=\"xtick_2\">\r\n     <g id=\"line2d_2\">\r\n      <path clip-path=\"url(#pbe2946be89)\" d=\"M 136.23 456.33 \r\nL 136.23 21.45 \r\n\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;\"/>\r\n     </g>\r\n     <g id=\"text_2\">\r\n      <!-- 0.2 -->\r\n      <g style=\"fill:#262626;\" transform=\"translate(127.98 473.3925)scale(0.11 -0.11)\">\r\n       <defs>\r\n        <path d=\"M 4.6875 3.90625 \r\nQ 5.078125 9.765625 10.15625 14.453125 \r\nQ 15.234375 19.140625 23.046875 29.09375 \r\nQ 30.859375 39.0625 33.203125 44.53125 \r\nQ 35.546875 50 34.953125 53.90625 \r\nQ 34.375 57.8125 31.25 60.34375 \r\nQ 28.125 62.890625 24.015625 62.5 \r\nQ 19.921875 62.109375 16.203125 59.375 \r\nQ 12.5 56.640625 10.546875 51.171875 \r\nL 3.125 52.34375 \r\nQ 6.25 61.328125 11.125 65.421875 \r\nQ 16.015625 69.53125 22.65625 69.921875 \r\nQ 26.5625 70.3125 29.6875 69.71875 \r\nQ 32.8125 69.140625 36.125 66.984375 \r\nQ 39.453125 64.84375 41.59375 60.546875 \r\nQ 43.75 56.25 43.15625 50.1875 \r\nQ 42.578125 44.140625 37.109375 35.734375 \r\nQ 31.640625 27.34375 16.015625 9.375 \r\nL 44.140625 9.375 \r\nL 44.140625 2.34375 \r\nL 4.6875 2.34375 \r\nz\r\n\" id=\"SimHei-50\"/>\r\n       </defs>\r\n       <use xlink:href=\"#SimHei-48\"/>\r\n       <use x=\"50\" xlink:href=\"#SimHei-46\"/>\r\n       <use x=\"100\" xlink:href=\"#SimHei-50\"/>\r\n      </g>\r\n     </g>\r\n    </g>\r\n    <g id=\"xtick_3\">\r\n     <g id=\"line2d_3\">\r\n      <path clip-path=\"url(#pbe2946be89)\" d=\"M 225.51 456.33 \r\nL 225.51 21.45 \r\n\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;\"/>\r\n     </g>\r\n     <g id=\"text_3\">\r\n      <!-- 0.4 -->\r\n      <g style=\"fill:#262626;\" transform=\"translate(217.26 473.3925)scale(0.11 -0.11)\">\r\n       <defs>\r\n        <path d=\"M 31.25 17.1875 \r\nL 1.171875 17.1875 \r\nL 1.171875 23.828125 \r\nL 32.8125 69.53125 \r\nL 38.671875 69.53125 \r\nL 38.671875 23.828125 \r\nL 48.046875 23.828125 \r\nL 48.046875 17.1875 \r\nL 38.671875 17.1875 \r\nL 38.671875 2.34375 \r\nL 31.25 2.34375 \r\nz\r\nM 31.25 23.828125 \r\nL 31.25 54.6875 \r\nL 9.375 23.828125 \r\nz\r\n\" id=\"SimHei-52\"/>\r\n       </defs>\r\n       <use xlink:href=\"#SimHei-48\"/>\r\n       <use x=\"50\" xlink:href=\"#SimHei-46\"/>\r\n       <use x=\"100\" xlink:href=\"#SimHei-52\"/>\r\n      </g>\r\n     </g>\r\n    </g>\r\n    <g id=\"xtick_4\">\r\n     <g id=\"line2d_4\">\r\n      <path clip-path=\"url(#pbe2946be89)\" d=\"M 314.79 456.33 \r\nL 314.79 21.45 \r\n\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;\"/>\r\n     </g>\r\n     <g id=\"text_4\">\r\n      <!-- 0.6 -->\r\n      <g style=\"fill:#262626;\" transform=\"translate(306.54 473.3925)scale(0.11 -0.11)\">\r\n       <defs>\r\n        <path d=\"M 3.515625 19.53125 \r\nQ 4.296875 30.859375 6.046875 34.765625 \r\nQ 7.8125 38.671875 11.328125 44.53125 \r\nL 27.34375 69.53125 \r\nL 36.328125 69.53125 \r\nL 19.921875 43.75 \r\nQ 30.46875 46.484375 36.71875 42.96875 \r\nQ 42.96875 39.453125 45.109375 34.953125 \r\nQ 47.265625 30.46875 47.453125 25.1875 \r\nQ 47.65625 19.921875 45.890625 14.84375 \r\nQ 44.140625 9.765625 39.640625 5.65625 \r\nQ 35.15625 1.5625 27.140625 1.171875 \r\nQ 19.140625 0.78125 13.46875 4.09375 \r\nQ 7.8125 7.421875 5.65625 13.46875 \r\nQ 3.515625 19.53125 4.296875 30.859375 \r\nz\r\nM 12.5 16.015625 \r\nQ 19.53125 8.59375 25.390625 8.203125 \r\nQ 31.25 7.8125 35.15625 12.109375 \r\nQ 39.0625 16.40625 39.0625 24.609375 \r\nQ 39.0625 32.8125 34.171875 35.9375 \r\nQ 29.296875 39.0625 23.234375 38.28125 \r\nQ 17.1875 37.5 14.453125 32.421875 \r\nQ 11.71875 27.34375 12.109375 21.671875 \r\nQ 12.5 16.015625 19.53125 8.59375 \r\nz\r\n\" id=\"SimHei-54\"/>\r\n       </defs>\r\n       <use xlink:href=\"#SimHei-48\"/>\r\n       <use x=\"50\" xlink:href=\"#SimHei-46\"/>\r\n       <use x=\"100\" xlink:href=\"#SimHei-54\"/>\r\n      </g>\r\n     </g>\r\n    </g>\r\n    <g id=\"xtick_5\">\r\n     <g id=\"line2d_5\">\r\n      <path clip-path=\"url(#pbe2946be89)\" d=\"M 404.07 456.33 \r\nL 404.07 21.45 \r\n\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;\"/>\r\n     </g>\r\n     <g id=\"text_5\">\r\n      <!-- 0.8 -->\r\n      <g style=\"fill:#262626;\" transform=\"translate(395.82 473.3925)scale(0.11 -0.11)\">\r\n       <defs>\r\n        <path d=\"M 2.734375 16.796875 \r\nQ 2.734375 26.171875 5.078125 30.65625 \r\nQ 7.421875 35.15625 12.890625 37.890625 \r\nQ 8.203125 40.625 6.640625 43.9375 \r\nQ 5.078125 47.265625 4.875 51.5625 \r\nQ 4.6875 55.859375 6.046875 58.984375 \r\nQ 7.421875 62.109375 10.15625 64.84375 \r\nQ 12.890625 67.578125 16.203125 68.546875 \r\nQ 19.53125 69.53125 23.4375 69.53125 \r\nQ 27.34375 69.53125 30.46875 68.75 \r\nQ 33.59375 67.96875 37.109375 65.421875 \r\nQ 40.625 62.890625 42.1875 58.203125 \r\nQ 43.75 53.515625 41.984375 47.265625 \r\nQ 40.234375 41.015625 32.8125 37.5 \r\nQ 39.453125 35.546875 42.1875 31.4375 \r\nQ 44.921875 27.34375 44.921875 21.484375 \r\nQ 44.921875 15.625 43.15625 12.109375 \r\nQ 41.40625 8.59375 39.25 6.25 \r\nQ 37.109375 3.90625 33.390625 2.53125 \r\nQ 29.6875 1.171875 24.015625 1.171875 \r\nQ 18.359375 1.171875 14.25 2.53125 \r\nQ 10.15625 3.90625 7.421875 6.640625 \r\nQ 4.6875 9.375 3.703125 13.078125 \r\nQ 2.734375 16.796875 2.734375 26.171875 \r\nz\r\nM 10.9375 26.5625 \r\nQ 10.546875 17.1875 12.296875 13.671875 \r\nQ 14.0625 10.15625 18.75 9.171875 \r\nQ 23.4375 8.203125 28.515625 9.375 \r\nQ 33.59375 10.546875 35.546875 14.84375 \r\nQ 37.5 19.140625 36.90625 23.4375 \r\nQ 36.328125 27.734375 32.03125 30.65625 \r\nQ 27.734375 33.59375 22.65625 33.203125 \r\nQ 17.578125 32.8125 14.25 29.6875 \r\nQ 10.9375 26.5625 10.546875 17.1875 \r\nz\r\nM 12.109375 56.25 \r\nQ 12.109375 48.4375 14.84375 44.921875 \r\nQ 17.578125 41.40625 23.4375 41.40625 \r\nQ 29.296875 41.40625 32.21875 44.921875 \r\nQ 35.15625 48.4375 34.953125 53.3125 \r\nQ 34.765625 58.203125 31.4375 60.546875 \r\nQ 28.125 62.890625 22.453125 62.5 \r\nQ 16.796875 62.109375 14.453125 59.171875 \r\nQ 12.109375 56.25 12.109375 48.4375 \r\nz\r\n\" id=\"SimHei-56\"/>\r\n       </defs>\r\n       <use xlink:href=\"#SimHei-48\"/>\r\n       <use x=\"50\" xlink:href=\"#SimHei-46\"/>\r\n       <use x=\"100\" xlink:href=\"#SimHei-56\"/>\r\n      </g>\r\n     </g>\r\n    </g>\r\n    <g id=\"xtick_6\">\r\n     <g id=\"line2d_6\">\r\n      <path clip-path=\"url(#pbe2946be89)\" d=\"M 493.35 456.33 \r\nL 493.35 21.45 \r\n\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;\"/>\r\n     </g>\r\n     <g id=\"text_6\">\r\n      <!-- 1.0 -->\r\n      <g style=\"fill:#262626;\" transform=\"translate(485.1 473.3925)scale(0.11 -0.11)\">\r\n       <defs>\r\n        <path d=\"M 21.875 56.25 \r\nQ 16.796875 51.171875 8.984375 46.484375 \r\nL 8.984375 53.90625 \r\nQ 18.75 60.546875 25 69.53125 \r\nL 29.6875 69.53125 \r\nL 29.6875 2.34375 \r\nL 21.875 2.34375 \r\nz\r\n\" id=\"SimHei-49\"/>\r\n       </defs>\r\n       <use xlink:href=\"#SimHei-49\"/>\r\n       <use x=\"50\" xlink:href=\"#SimHei-46\"/>\r\n       <use x=\"100\" xlink:href=\"#SimHei-48\"/>\r\n      </g>\r\n     </g>\r\n    </g>\r\n    <g id=\"text_7\">\r\n     <!-- False Positive Rate -->\r\n     <g style=\"fill:#262626;\" transform=\"translate(213.15 487.0175)scale(0.12 -0.12)\">\r\n      <defs>\r\n       <path d=\"M 45.703125 61.328125 \r\nL 13.671875 61.328125 \r\nL 13.671875 39.453125 \r\nL 37.890625 39.453125 \r\nL 37.890625 32.03125 \r\nL 13.671875 32.03125 \r\nL 13.671875 1.953125 \r\nL 4.6875 1.953125 \r\nL 4.6875 68.75 \r\nL 45.703125 68.75 \r\nz\r\n\" id=\"SimHei-70\"/>\r\n       <path d=\"M 44.921875 1.953125 \r\nL 35.546875 1.953125 \r\nQ 34.765625 2.734375 34.375 4.09375 \r\nQ 33.984375 5.46875 33.984375 7.421875 \r\nQ 31.25 4.296875 27.34375 2.734375 \r\nQ 23.4375 1.171875 19.140625 1.171875 \r\nQ 12.890625 1.171875 8.59375 4.296875 \r\nQ 4.296875 7.421875 4.296875 13.28125 \r\nQ 4.296875 19.140625 8.203125 22.65625 \r\nQ 12.109375 26.171875 20.3125 27.34375 \r\nQ 25.78125 28.125 29.875 29.296875 \r\nQ 33.984375 30.46875 33.984375 32.421875 \r\nQ 33.984375 34.765625 32.21875 37.109375 \r\nQ 30.46875 39.453125 24.609375 39.453125 \r\nQ 19.921875 39.453125 17.765625 37.6875 \r\nQ 15.625 35.9375 14.84375 32.8125 \r\nL 6.25 32.8125 \r\nQ 7.03125 39.0625 11.90625 42.765625 \r\nQ 16.796875 46.484375 24.609375 46.484375 \r\nQ 33.203125 46.484375 37.5 42.578125 \r\nQ 41.796875 38.671875 41.796875 31.640625 \r\nL 41.796875 10.15625 \r\nQ 41.796875 7.8125 42.578125 5.859375 \r\nQ 43.359375 3.90625 44.921875 1.953125 \r\nz\r\nM 33.984375 16.40625 \r\nL 33.984375 24.21875 \r\nQ 31.640625 23.4375 29.484375 22.84375 \r\nQ 27.34375 22.265625 22.265625 21.484375 \r\nQ 16.40625 20.703125 14.640625 18.75 \r\nQ 12.890625 16.796875 12.890625 14.0625 \r\nQ 12.890625 11.71875 14.640625 9.953125 \r\nQ 16.40625 8.203125 19.921875 8.203125 \r\nQ 23.4375 8.203125 27.53125 10.15625 \r\nQ 31.640625 12.109375 33.984375 16.40625 \r\nz\r\n\" id=\"SimHei-97\"/>\r\n       <path d=\"M 28.515625 1.953125 \r\nL 20.703125 1.953125 \r\nL 20.703125 68.75 \r\nL 28.515625 68.75 \r\nz\r\n\" id=\"SimHei-108\"/>\r\n       <path d=\"M 42.96875 14.0625 \r\nQ 42.96875 7.8125 38.078125 4.484375 \r\nQ 33.203125 1.171875 25.78125 1.171875 \r\nQ 16.40625 1.171875 11.328125 4.875 \r\nQ 6.25 8.59375 6.25 15.625 \r\nL 14.0625 15.625 \r\nQ 14.0625 10.9375 17.375 9.375 \r\nQ 20.703125 7.8125 25.390625 7.8125 \r\nQ 30.078125 7.8125 32.421875 9.5625 \r\nQ 34.765625 11.328125 34.765625 14.0625 \r\nQ 34.765625 16.015625 32.8125 17.96875 \r\nQ 30.859375 19.921875 23.046875 21.09375 \r\nQ 14.0625 22.265625 10.734375 25.578125 \r\nQ 7.421875 28.90625 7.421875 34.375 \r\nQ 7.421875 39.0625 11.90625 42.765625 \r\nQ 16.40625 46.484375 25 46.484375 \r\nQ 32.8125 46.484375 37.296875 42.96875 \r\nQ 41.796875 39.453125 41.796875 33.59375 \r\nL 33.984375 33.59375 \r\nQ 33.984375 37.109375 31.4375 38.46875 \r\nQ 28.90625 39.84375 25 39.84375 \r\nQ 19.921875 39.84375 17.765625 38.078125 \r\nQ 15.625 36.328125 15.625 33.984375 \r\nQ 15.625 31.25 17.578125 29.6875 \r\nQ 19.53125 28.125 25.78125 27.34375 \r\nQ 35.9375 25.78125 39.453125 22.453125 \r\nQ 42.96875 19.140625 42.96875 14.0625 \r\nz\r\n\" id=\"SimHei-115\"/>\r\n       <path d=\"M 44.53125 16.796875 \r\nQ 43.75 9.765625 38.28125 5.46875 \r\nQ 32.8125 1.171875 25.390625 1.171875 \r\nQ 16.015625 1.171875 9.953125 7.21875 \r\nQ 3.90625 13.28125 3.90625 23.828125 \r\nQ 3.90625 34.375 9.953125 40.421875 \r\nQ 16.015625 46.484375 25.390625 46.484375 \r\nQ 33.59375 46.484375 38.859375 41.203125 \r\nQ 44.140625 35.9375 44.140625 23.828125 \r\nL 12.5 23.828125 \r\nQ 12.5 15.234375 16.203125 11.71875 \r\nQ 19.921875 8.203125 25.390625 8.203125 \r\nQ 29.6875 8.203125 32.421875 10.34375 \r\nQ 35.15625 12.5 35.9375 16.796875 \r\nz\r\nM 35.15625 30.078125 \r\nQ 34.375 35.546875 31.640625 37.6875 \r\nQ 28.90625 39.84375 24.609375 39.84375 \r\nQ 20.703125 39.84375 17.578125 37.6875 \r\nQ 14.453125 35.546875 12.890625 30.078125 \r\nz\r\n\" id=\"SimHei-101\"/>\r\n       <path id=\"SimHei-32\"/>\r\n       <path d=\"M 46.09375 48.4375 \r\nQ 46.09375 39.0625 40.625 33.59375 \r\nQ 35.15625 28.125 25.390625 28.125 \r\nL 14.0625 28.125 \r\nL 14.0625 1.953125 \r\nL 5.078125 1.953125 \r\nL 5.078125 68.75 \r\nL 25.390625 68.75 \r\nQ 35.15625 68.75 40.625 63.28125 \r\nQ 46.09375 57.8125 46.09375 48.4375 \r\nz\r\nM 37.109375 48.4375 \r\nQ 37.109375 55.859375 33.59375 58.59375 \r\nQ 30.078125 61.328125 23.046875 61.328125 \r\nL 14.0625 61.328125 \r\nL 14.0625 35.546875 \r\nL 23.046875 35.546875 \r\nQ 30.078125 35.546875 33.59375 38.28125 \r\nQ 37.109375 41.015625 37.109375 48.4375 \r\nz\r\n\" id=\"SimHei-80\"/>\r\n       <path d=\"M 45.703125 23.828125 \r\nQ 45.703125 13.671875 39.453125 7.421875 \r\nQ 33.203125 1.171875 24.609375 1.171875 \r\nQ 16.015625 1.171875 9.765625 7.421875 \r\nQ 3.515625 13.671875 3.515625 23.828125 \r\nQ 3.515625 33.984375 9.765625 40.234375 \r\nQ 16.015625 46.484375 24.609375 46.484375 \r\nQ 33.203125 46.484375 39.453125 40.234375 \r\nQ 45.703125 33.984375 45.703125 23.828125 \r\nz\r\nM 37.109375 23.828125 \r\nQ 37.109375 31.640625 33.203125 35.546875 \r\nQ 29.296875 39.453125 24.609375 39.453125 \r\nQ 19.921875 39.453125 16.015625 35.546875 \r\nQ 12.109375 31.640625 12.109375 23.828125 \r\nQ 12.109375 16.015625 16.015625 12.109375 \r\nQ 19.921875 8.203125 24.609375 8.203125 \r\nQ 29.296875 8.203125 33.203125 12.109375 \r\nQ 37.109375 16.015625 37.109375 23.828125 \r\nz\r\n\" id=\"SimHei-111\"/>\r\n       <path d=\"M 28.125 58.203125 \r\nL 20.3125 58.203125 \r\nL 20.3125 68.359375 \r\nL 28.125 68.359375 \r\nz\r\nM 28.125 1.953125 \r\nL 20.3125 1.953125 \r\nL 20.3125 45.703125 \r\nL 28.125 45.703125 \r\nz\r\n\" id=\"SimHei-105\"/>\r\n       <path d=\"M 42.96875 3.125 \r\nQ 41.015625 2.34375 38.46875 1.75 \r\nQ 35.9375 1.171875 31.640625 1.171875 \r\nQ 24.609375 1.171875 20.3125 5.078125 \r\nQ 16.015625 8.984375 16.015625 16.015625 \r\nL 16.015625 39.453125 \r\nL 2.734375 39.453125 \r\nL 2.734375 45.703125 \r\nL 16.015625 45.703125 \r\nL 16.015625 60.9375 \r\nL 23.828125 60.9375 \r\nL 23.828125 45.703125 \r\nL 39.84375 45.703125 \r\nL 39.84375 39.453125 \r\nL 23.828125 39.453125 \r\nL 23.828125 15.625 \r\nQ 23.828125 12.5 25.390625 10.34375 \r\nQ 26.953125 8.203125 31.25 8.203125 \r\nQ 35.546875 8.203125 38.28125 8.984375 \r\nQ 41.015625 9.765625 42.96875 10.9375 \r\nz\r\n\" id=\"SimHei-116\"/>\r\n       <path d=\"M 44.921875 45.703125 \r\nL 28.515625 1.171875 \r\nL 19.921875 1.171875 \r\nL 3.515625 45.703125 \r\nL 11.71875 45.703125 \r\nL 23.828125 11.71875 \r\nL 24.609375 11.71875 \r\nL 36.71875 45.703125 \r\nz\r\n\" id=\"SimHei-118\"/>\r\n       <path d=\"M 46.875 1.953125 \r\nL 37.5 1.953125 \r\nL 23.4375 30.859375 \r\nL 13.28125 30.859375 \r\nL 13.28125 1.953125 \r\nL 4.296875 1.953125 \r\nL 4.296875 68.75 \r\nL 23.828125 68.75 \r\nQ 33.203125 68.75 39.0625 64.25 \r\nQ 44.921875 59.765625 44.921875 49.609375 \r\nQ 44.921875 41.796875 41.015625 37.5 \r\nQ 37.109375 33.203125 32.03125 32.03125 \r\nz\r\nM 35.9375 49.609375 \r\nQ 35.9375 55.078125 32.609375 58.203125 \r\nQ 29.296875 61.328125 21.875 61.328125 \r\nL 13.28125 61.328125 \r\nL 13.28125 38.28125 \r\nL 24.21875 38.28125 \r\nQ 28.90625 38.28125 32.421875 40.8125 \r\nQ 35.9375 43.359375 35.9375 49.609375 \r\nz\r\n\" id=\"SimHei-82\"/>\r\n      </defs>\r\n      <use xlink:href=\"#SimHei-70\"/>\r\n      <use x=\"50\" xlink:href=\"#SimHei-97\"/>\r\n      <use x=\"100\" xlink:href=\"#SimHei-108\"/>\r\n      <use x=\"150\" xlink:href=\"#SimHei-115\"/>\r\n      <use x=\"200\" xlink:href=\"#SimHei-101\"/>\r\n      <use x=\"250\" xlink:href=\"#SimHei-32\"/>\r\n      <use x=\"300\" xlink:href=\"#SimHei-80\"/>\r\n      <use x=\"350\" xlink:href=\"#SimHei-111\"/>\r\n      <use x=\"400\" xlink:href=\"#SimHei-115\"/>\r\n      <use x=\"450\" xlink:href=\"#SimHei-105\"/>\r\n      <use x=\"500\" xlink:href=\"#SimHei-116\"/>\r\n      <use x=\"550\" xlink:href=\"#SimHei-105\"/>\r\n      <use x=\"600\" xlink:href=\"#SimHei-118\"/>\r\n      <use x=\"650\" xlink:href=\"#SimHei-101\"/>\r\n      <use x=\"700\" xlink:href=\"#SimHei-32\"/>\r\n      <use x=\"750\" xlink:href=\"#SimHei-82\"/>\r\n      <use x=\"800\" xlink:href=\"#SimHei-97\"/>\r\n      <use x=\"850\" xlink:href=\"#SimHei-116\"/>\r\n      <use x=\"900\" xlink:href=\"#SimHei-101\"/>\r\n     </g>\r\n    </g>\r\n   </g>\r\n   <g id=\"matplotlib.axis_2\">\r\n    <g id=\"ytick_1\">\r\n     <g id=\"line2d_7\">\r\n      <path clip-path=\"url(#pbe2946be89)\" d=\"M 46.95 456.33 \r\nL 493.35 456.33 \r\n\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;\"/>\r\n     </g>\r\n     <g id=\"text_8\">\r\n      <!-- 0.0 -->\r\n      <g style=\"fill:#262626;\" transform=\"translate(20.95 460.11125)scale(0.11 -0.11)\">\r\n       <use xlink:href=\"#SimHei-48\"/>\r\n       <use x=\"50\" xlink:href=\"#SimHei-46\"/>\r\n       <use x=\"100\" xlink:href=\"#SimHei-48\"/>\r\n      </g>\r\n     </g>\r\n    </g>\r\n    <g id=\"ytick_2\">\r\n     <g id=\"line2d_8\">\r\n      <path clip-path=\"url(#pbe2946be89)\" d=\"M 46.95 369.354 \r\nL 493.35 369.354 \r\n\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;\"/>\r\n     </g>\r\n     <g id=\"text_9\">\r\n      <!-- 0.2 -->\r\n      <g style=\"fill:#262626;\" transform=\"translate(20.95 373.13525)scale(0.11 -0.11)\">\r\n       <use xlink:href=\"#SimHei-48\"/>\r\n       <use x=\"50\" xlink:href=\"#SimHei-46\"/>\r\n       <use x=\"100\" xlink:href=\"#SimHei-50\"/>\r\n      </g>\r\n     </g>\r\n    </g>\r\n    <g id=\"ytick_3\">\r\n     <g id=\"line2d_9\">\r\n      <path clip-path=\"url(#pbe2946be89)\" d=\"M 46.95 282.378 \r\nL 493.35 282.378 \r\n\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;\"/>\r\n     </g>\r\n     <g id=\"text_10\">\r\n      <!-- 0.4 -->\r\n      <g style=\"fill:#262626;\" transform=\"translate(20.95 286.15925)scale(0.11 -0.11)\">\r\n       <use xlink:href=\"#SimHei-48\"/>\r\n       <use x=\"50\" xlink:href=\"#SimHei-46\"/>\r\n       <use x=\"100\" xlink:href=\"#SimHei-52\"/>\r\n      </g>\r\n     </g>\r\n    </g>\r\n    <g id=\"ytick_4\">\r\n     <g id=\"line2d_10\">\r\n      <path clip-path=\"url(#pbe2946be89)\" d=\"M 46.95 195.402 \r\nL 493.35 195.402 \r\n\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;\"/>\r\n     </g>\r\n     <g id=\"text_11\">\r\n      <!-- 0.6 -->\r\n      <g style=\"fill:#262626;\" transform=\"translate(20.95 199.18325)scale(0.11 -0.11)\">\r\n       <use xlink:href=\"#SimHei-48\"/>\r\n       <use x=\"50\" xlink:href=\"#SimHei-46\"/>\r\n       <use x=\"100\" xlink:href=\"#SimHei-54\"/>\r\n      </g>\r\n     </g>\r\n    </g>\r\n    <g id=\"ytick_5\">\r\n     <g id=\"line2d_11\">\r\n      <path clip-path=\"url(#pbe2946be89)\" d=\"M 46.95 108.426 \r\nL 493.35 108.426 \r\n\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;\"/>\r\n     </g>\r\n     <g id=\"text_12\">\r\n      <!-- 0.8 -->\r\n      <g style=\"fill:#262626;\" transform=\"translate(20.95 112.20725)scale(0.11 -0.11)\">\r\n       <use xlink:href=\"#SimHei-48\"/>\r\n       <use x=\"50\" xlink:href=\"#SimHei-46\"/>\r\n       <use x=\"100\" xlink:href=\"#SimHei-56\"/>\r\n      </g>\r\n     </g>\r\n    </g>\r\n    <g id=\"ytick_6\">\r\n     <g id=\"line2d_12\">\r\n      <path clip-path=\"url(#pbe2946be89)\" d=\"M 46.95 21.45 \r\nL 493.35 21.45 \r\n\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;\"/>\r\n     </g>\r\n     <g id=\"text_13\">\r\n      <!-- 1.0 -->\r\n      <g style=\"fill:#262626;\" transform=\"translate(20.95 25.23125)scale(0.11 -0.11)\">\r\n       <use xlink:href=\"#SimHei-49\"/>\r\n       <use x=\"50\" xlink:href=\"#SimHei-46\"/>\r\n       <use x=\"100\" xlink:href=\"#SimHei-48\"/>\r\n      </g>\r\n     </g>\r\n    </g>\r\n    <g id=\"text_14\">\r\n     <!-- True Positive Rate -->\r\n     <g style=\"fill:#262626;\" transform=\"translate(15.45 292.89)rotate(-90)scale(0.12 -0.12)\">\r\n      <defs>\r\n       <path d=\"M 44.53125 61.328125 \r\nL 28.90625 61.328125 \r\nL 28.90625 1.953125 \r\nL 19.921875 1.953125 \r\nL 19.921875 61.328125 \r\nL 4.296875 61.328125 \r\nL 4.296875 68.75 \r\nL 44.53125 68.75 \r\nz\r\n\" id=\"SimHei-84\"/>\r\n       <path d=\"M 39.0625 37.890625 \r\nQ 31.640625 39.0625 26.5625 35.734375 \r\nQ 21.484375 32.421875 17.96875 24.21875 \r\nL 17.96875 1.953125 \r\nL 10.15625 1.953125 \r\nL 10.15625 45.703125 \r\nL 17.96875 45.703125 \r\nL 17.96875 34.375 \r\nQ 21.484375 40.625 26.75 43.546875 \r\nQ 32.03125 46.484375 39.0625 46.484375 \r\nz\r\n\" id=\"SimHei-114\"/>\r\n       <path d=\"M 43.75 1.953125 \r\nL 35.9375 1.953125 \r\nL 35.9375 10.15625 \r\nQ 32.8125 5.859375 29.09375 3.515625 \r\nQ 25.390625 1.171875 19.53125 1.171875 \r\nQ 12.5 1.171875 8.984375 5.078125 \r\nQ 5.46875 8.984375 5.46875 14.84375 \r\nL 5.46875 45.703125 \r\nL 13.28125 45.703125 \r\nL 13.28125 17.578125 \r\nQ 13.28125 12.890625 15.625 10.15625 \r\nQ 17.96875 7.421875 21.875 7.421875 \r\nQ 26.953125 7.421875 31.4375 12.6875 \r\nQ 35.9375 17.96875 35.9375 25.78125 \r\nL 35.9375 45.703125 \r\nL 43.75 45.703125 \r\nz\r\n\" id=\"SimHei-117\"/>\r\n      </defs>\r\n      <use xlink:href=\"#SimHei-84\"/>\r\n      <use x=\"50\" xlink:href=\"#SimHei-114\"/>\r\n      <use x=\"100\" xlink:href=\"#SimHei-117\"/>\r\n      <use x=\"150\" xlink:href=\"#SimHei-101\"/>\r\n      <use x=\"200\" xlink:href=\"#SimHei-32\"/>\r\n      <use x=\"250\" xlink:href=\"#SimHei-80\"/>\r\n      <use x=\"300\" xlink:href=\"#SimHei-111\"/>\r\n      <use x=\"350\" xlink:href=\"#SimHei-115\"/>\r\n      <use x=\"400\" xlink:href=\"#SimHei-105\"/>\r\n      <use x=\"450\" xlink:href=\"#SimHei-116\"/>\r\n      <use x=\"500\" xlink:href=\"#SimHei-105\"/>\r\n      <use x=\"550\" xlink:href=\"#SimHei-118\"/>\r\n      <use x=\"600\" xlink:href=\"#SimHei-101\"/>\r\n      <use x=\"650\" xlink:href=\"#SimHei-32\"/>\r\n      <use x=\"700\" xlink:href=\"#SimHei-82\"/>\r\n      <use x=\"750\" xlink:href=\"#SimHei-97\"/>\r\n      <use x=\"800\" xlink:href=\"#SimHei-116\"/>\r\n      <use x=\"850\" xlink:href=\"#SimHei-101\"/>\r\n     </g>\r\n    </g>\r\n   </g>\r\n   <g id=\"line2d_13\">\r\n    <path clip-path=\"url(#pbe2946be89)\" d=\"M 46.95 456.33 \r\nL 47.054033 455.017485 \r\nL 47.072125 454.908109 \r\nL 47.180681 453.869034 \r\nL 47.198774 453.759658 \r\nL 47.30733 452.611207 \r\nL 47.320899 452.556519 \r\nL 47.429455 451.335151 \r\nL 47.456594 451.225775 \r\nL 47.56515 450.241388 \r\nL 47.610382 450.168471 \r\nL 47.718938 449.293461 \r\nL 47.723461 449.293461 \r\nL 47.818447 448.254386 \r\nL 47.845586 448.14501 \r\nL 47.954142 447.251771 \r\nL 47.972235 447.160624 \r\nL 48.080791 446.121549 \r\nL 48.09436 446.121549 \r\nL 48.202916 445.21008 \r\nL 48.243625 445.100704 \r\nL 48.352181 444.33507 \r\nL 48.388366 444.225694 \r\nL 48.492399 443.660584 \r\nL 48.533107 443.551207 \r\nL 48.641663 442.822032 \r\nL 48.664279 442.785573 \r\nL 48.772835 442.01994 \r\nL 48.790927 441.928793 \r\nL 48.89496 440.926177 \r\nL 48.913053 440.871489 \r\nL 49.021609 440.26992 \r\nL 49.044224 440.178773 \r\nL 49.15278 439.686579 \r\nL 49.161827 439.686579 \r\nL 49.270383 438.957404 \r\nL 49.306568 438.884487 \r\nL 49.410601 438.082394 \r\nL 49.42417 438.027706 \r\nL 49.532726 437.116237 \r\nL 49.546296 437.025091 \r\nL 49.641282 436.204769 \r\nL 49.68199 436.113622 \r\nL 49.790546 435.439135 \r\nL 49.808639 435.347988 \r\nL 49.912672 434.454748 \r\nL 49.939811 434.345372 \r\nL 50.048367 433.579738 \r\nL 50.075506 433.506821 \r\nL 50.184062 432.996398 \r\nL 50.197631 432.923481 \r\nL 50.306187 432.321911 \r\nL 50.319756 432.248994 \r\nL 50.423789 431.446901 \r\nL 50.459974 431.355755 \r\nL 50.56853 430.845332 \r\nL 50.604716 430.735956 \r\nL 50.704225 430.152616 \r\nL 50.726841 430.043239 \r\nL 50.830874 429.551046 \r\nL 50.85349 429.478129 \r\nL 50.93943 429.022394 \r\nL 50.984661 428.913018 \r\nL 51.084171 428.402596 \r\nL 51.120356 428.293219 \r\nL 51.228912 427.873944 \r\nL 51.251528 427.782797 \r\nL 51.360084 427.162998 \r\nL 51.396269 427.071851 \r\nL 51.500302 426.470282 \r\nL 51.513871 426.397364 \r\nL 51.613381 425.814024 \r\nL 51.64052 425.741107 \r\nL 51.74003 425.139537 \r\nL 51.785261 425.030161 \r\nL 51.893817 424.46505 \r\nL 51.907387 424.373903 \r\nL 52.015943 423.754105 \r\nL 52.061174 423.644728 \r\nL 52.165207 423.334829 \r\nL 52.201392 423.225453 \r\nL 52.296379 422.660342 \r\nL 52.332564 422.587425 \r\nL 52.436597 422.095231 \r\nL 52.472782 422.004085 \r\nL 52.581338 421.511891 \r\nL 52.603954 421.420744 \r\nL 52.71251 421.019698 \r\nL 52.721556 421.001469 \r\nL 52.825589 420.290523 \r\nL 52.866297 420.199376 \r\nL 52.95676 419.780101 \r\nL 53.024608 419.670724 \r\nL 53.133164 419.251449 \r\nL 53.146733 419.142072 \r\nL 53.255289 418.522274 \r\nL 53.300521 418.431127 \r\nL 53.40003 417.938934 \r\nL 53.436216 417.847787 \r\nL 53.544772 417.319135 \r\nL 53.603573 417.209759 \r\nL 53.698559 416.899859 \r\nL 53.743791 416.808712 \r\nL 53.8433 416.188913 \r\nL 53.884009 416.097767 \r\nL 53.988042 415.623803 \r\nL 54.04232 415.532656 \r\nL 54.132783 415.022233 \r\nL 54.173491 414.985775 \r\nL 54.277524 414.274829 \r\nL 54.322756 414.183682 \r\nL 54.426788 413.582113 \r\nL 54.490113 413.509195 \r\nL 54.598669 412.980543 \r\nL 54.607715 412.980543 \r\nL 54.711748 412.506579 \r\nL 54.761502 412.397203 \r\nL 54.870058 411.923239 \r\nL 54.928859 411.850322 \r\nL 55.028369 411.32167 \r\nL 55.060031 411.230523 \r\nL 55.168587 410.73833 \r\nL 55.195726 410.665412 \r\nL 55.304282 410.227907 \r\nL 55.331421 410.136761 \r\nL 55.412838 409.699256 \r\nL 55.453546 409.589879 \r\nL 55.562102 408.951851 \r\nL 55.611857 408.842475 \r\nL 55.711367 408.532575 \r\nL 55.78826 408.441429 \r\nL 55.896816 407.931006 \r\nL 55.933002 407.839859 \r\nL 56.032511 407.311207 \r\nL 56.077743 407.201831 \r\nL 56.181776 406.618491 \r\nL 56.23153 406.509115 \r\nL 56.335563 406.108068 \r\nL 56.403411 405.998692 \r\nL 56.511967 405.542958 \r\nL 56.561721 405.451811 \r\nL 56.670277 404.759095 \r\nL 56.710986 404.649718 \r\nL 56.819542 404.139296 \r\nL 56.86025 404.048149 \r\nL 56.968806 403.574185 \r\nL 57.050223 403.501268 \r\nL 57.149733 402.990845 \r\nL 57.199487 402.881469 \r\nL 57.308043 402.206982 \r\nL 57.339705 402.097606 \r\nL 57.443738 401.787706 \r\nL 57.479923 401.67833 \r\nL 57.588479 401.222596 \r\nL 57.633711 401.113219 \r\nL 57.737744 400.876237 \r\nL 57.801068 400.766861 \r\nL 57.909624 400.183521 \r\nL 57.963902 400.074145 \r\nL 58.072458 399.764245 \r\nL 58.113166 399.654869 \r\nL 58.221722 399.0533 \r\nL 58.239815 398.943924 \r\nL 58.325755 398.688712 \r\nL 58.411695 398.597565 \r\nL 58.511205 398.251207 \r\nL 58.592621 398.141831 \r\nL 58.701177 397.649638 \r\nL 58.746409 397.57672 \r\nL 58.854965 397.084527 \r\nL 58.913766 396.975151 \r\nL 59.017799 396.71994 \r\nL 59.040415 396.628793 \r\nL 59.148971 396.154829 \r\nL 59.185156 396.045453 \r\nL 59.289189 395.480342 \r\nL 59.343467 395.389195 \r\nL 59.438453 395.042837 \r\nL 59.470115 394.933461 \r\nL 59.578671 394.587103 \r\nL 59.592241 394.568873 \r\nL 59.700796 394.003763 \r\nL 59.727935 393.894386 \r\nL 59.836491 393.420423 \r\nL 59.872677 393.311046 \r\nL 59.981233 392.800624 \r\nL 60.012895 392.691247 \r\nL 60.121451 392.253742 \r\nL 60.166682 392.144366 \r\nL 60.257145 391.816237 \r\nL 60.293331 391.74332 \r\nL 60.397364 391.378732 \r\nL 60.460688 391.287586 \r\nL 60.569244 390.941227 \r\nL 60.628045 390.831851 \r\nL 60.727554 390.303199 \r\nL 60.818018 390.212052 \r\nL 60.926574 389.537565 \r\nL 60.940143 389.464648 \r\nL 61.044176 389.008913 \r\nL 61.066792 388.917767 \r\nL 61.170824 388.425573 \r\nL 61.202487 388.389115 \r\nL 61.311042 388.042757 \r\nL 61.360797 387.93338 \r\nL 61.469353 387.514105 \r\nL 61.519108 387.404728 \r\nL 61.627664 387.094829 \r\nL 61.663849 387.0766 \r\nL 61.745266 386.693783 \r\nL 61.817637 386.584406 \r\nL 61.926193 386.310966 \r\nL 61.948808 386.238048 \r\nL 62.052841 385.982837 \r\nL 62.09355 385.90992 \r\nL 62.16592 385.527103 \r\nL 62.220198 385.417726 \r\nL 62.328754 384.889074 \r\nL 62.405648 384.779698 \r\nL 62.500634 384.251046 \r\nL 62.53682 384.14167 \r\nL 62.645376 383.868229 \r\nL 62.713223 383.758853 \r\nL 62.817256 383.430724 \r\nL 62.857964 383.339577 \r\nL 62.961997 382.938531 \r\nL 63.034368 382.829155 \r\nL 63.129354 382.409879 \r\nL 63.192678 382.318732 \r\nL 63.287665 381.917686 \r\nL 63.332896 381.80831 \r\nL 63.436929 381.261429 \r\nL 63.500253 381.152052 \r\nL 63.604286 380.714547 \r\nL 63.649518 380.659859 \r\nL 63.749027 380.222354 \r\nL 63.821398 380.112978 \r\nL 63.929954 379.74839 \r\nL 63.961616 379.657243 \r\nL 64.070172 379.219738 \r\nL 64.115403 379.110362 \r\nL 64.219436 378.87338 \r\nL 64.260145 378.800463 \r\nL 64.355131 378.472334 \r\nL 64.386793 378.381187 \r\nL 64.486303 378.034829 \r\nL 64.517965 377.961911 \r\nL 64.603905 377.579095 \r\nL 64.658183 377.524406 \r\nL 64.766739 377.105131 \r\nL 64.843633 376.995755 \r\nL 64.934096 376.704085 \r\nL 64.974804 376.594708 \r\nL 65.08336 376.284809 \r\nL 65.115022 376.211891 \r\nL 65.210009 375.847304 \r\nL 65.264287 375.774386 \r\nL 65.363796 375.446258 \r\nL 65.458783 375.336881 \r\nL 65.562816 375.136358 \r\nL 65.594478 375.026982 \r\nL 65.703034 374.516559 \r\nL 65.739219 374.407183 \r\nL 65.779927 374.261348 \r\nL 65.906576 374.151972 \r\nL 66.006086 373.732696 \r\nL 66.028701 373.62332 \r\nL 66.128211 373.240503 \r\nL 66.218674 373.131127 \r\nL 66.32723 372.839457 \r\nL 66.367939 372.766539 \r\nL 66.476495 372.45664 \r\nL 66.557911 372.347264 \r\nL 66.652898 372.110282 \r\nL 66.707176 372.000905 \r\nL 66.815732 371.618089 \r\nL 66.838348 371.508712 \r\nL 66.946903 371.144125 \r\nL 67.023797 371.034748 \r\nL 67.12783 370.670161 \r\nL 67.186631 370.560785 \r\nL 67.295187 370.214427 \r\nL 67.38565 370.10505 \r\nL 67.48516 369.83161 \r\nL 67.516822 369.722233 \r\nL 67.620855 369.138893 \r\nL 67.652517 369.047746 \r\nL 67.761073 368.756076 \r\nL 67.837967 368.6467 \r\nL 67.946523 368.35503 \r\nL 67.960092 368.263883 \r\nL 68.059602 367.899296 \r\nL 68.11388 367.78992 \r\nL 68.217912 367.589396 \r\nL 68.249574 367.498249 \r\nL 68.349084 367.078974 \r\nL 68.385269 367.060744 \r\nL 68.493825 366.532093 \r\nL 68.534534 366.422716 \r\nL 68.64309 366.112817 \r\nL 68.665705 366.058129 \r\nL 68.774261 365.602394 \r\nL 68.819493 365.493018 \r\nL 68.923526 365.201348 \r\nL 68.982327 365.091972 \r\nL 69.090883 364.599779 \r\nL 69.113499 364.508632 \r\nL 69.217531 364.125815 \r\nL 69.235624 364.016439 \r\nL 69.339657 363.67008 \r\nL 69.384888 363.560704 \r\nL 69.493444 363.269034 \r\nL 69.538676 363.159658 \r\nL 69.647232 362.940905 \r\nL 69.683417 362.849759 \r\nL 69.791973 362.5034 \r\nL 69.832681 362.448712 \r\nL 69.936714 361.92006 \r\nL 70.004562 361.810684 \r\nL 70.113118 361.610161 \r\nL 70.167396 361.500785 \r\nL 70.275951 361.117968 \r\nL 70.325706 361.008592 \r\nL 70.434262 360.662233 \r\nL 70.479494 360.571087 \r\nL 70.579003 360.425252 \r\nL 70.646851 360.315875 \r\nL 70.750884 359.787223 \r\nL 70.800638 359.677847 \r\nL 70.909194 359.240342 \r\nL 70.986088 359.130966 \r\nL 71.085598 358.912213 \r\nL 71.144399 358.802837 \r\nL 71.243908 358.274185 \r\nL 71.27557 358.183038 \r\nL 71.379603 357.781992 \r\nL 71.501729 357.672616 \r\nL 71.592192 357.344487 \r\nL 71.678132 357.271569 \r\nL 71.786688 356.651771 \r\nL 71.822873 356.597082 \r\nL 71.926906 356.268954 \r\nL 71.99023 356.159577 \r\nL 72.094263 355.758531 \r\nL 72.153064 355.649155 \r\nL 72.257097 355.248109 \r\nL 72.34756 355.138732 \r\nL 72.451593 354.938209 \r\nL 72.546579 354.828833 \r\nL 72.646089 354.573622 \r\nL 72.745598 354.464245 \r\nL 72.854154 354.209034 \r\nL 72.881293 354.117887 \r\nL 72.989849 353.607465 \r\nL 73.098405 353.498089 \r\nL 73.202438 353.115272 \r\nL 73.256716 353.042354 \r\nL 73.365272 352.805372 \r\nL 73.415027 352.732455 \r\nL 73.50549 352.331408 \r\nL 73.618569 352.222032 \r\nL 73.718078 352.021509 \r\nL 73.767833 351.930362 \r\nL 73.853773 351.638692 \r\nL 73.908051 351.529316 \r\nL 74.012084 351.164728 \r\nL 74.102547 351.055352 \r\nL 74.211103 350.8366 \r\nL 74.224673 350.745453 \r\nL 74.328705 350.472012 \r\nL 74.360368 350.380865 \r\nL 74.4644 350.143883 \r\nL 74.554864 350.034507 \r\nL 74.658896 349.66992 \r\nL 74.722221 349.597002 \r\nL 74.82173 349.268873 \r\nL 74.961948 349.159497 \r\nL 75.065981 348.649074 \r\nL 75.142875 348.539698 \r\nL 75.233338 348.375634 \r\nL 75.323801 348.284487 \r\nL 75.418788 347.919899 \r\nL 75.509251 347.810523 \r\nL 75.608761 347.31833 \r\nL 75.667562 347.227183 \r\nL 75.776118 346.917284 \r\nL 75.862058 346.807907 \r\nL 75.952521 346.461549 \r\nL 76.029415 346.352173 \r\nL 76.124401 346.005815 \r\nL 76.160586 345.932897 \r\nL 76.255573 345.55008 \r\nL 76.355082 345.440704 \r\nL 76.463638 345.076117 \r\nL 76.572194 344.98497 \r\nL 76.671704 344.784447 \r\nL 76.716936 344.67507 \r\nL 76.811922 344.3834 \r\nL 76.915955 344.274024 \r\nL 77.024511 344.000584 \r\nL 77.047126 343.891207 \r\nL 77.146636 343.654225 \r\nL 77.187344 343.544849 \r\nL 77.2959 343.21672 \r\nL 77.345655 343.107344 \r\nL 77.449688 342.797445 \r\nL 77.585383 342.688068 \r\nL 77.693939 342.287022 \r\nL 77.734647 342.177646 \r\nL 77.843203 341.977123 \r\nL 77.888435 341.867746 \r\nL 77.992467 341.4667 \r\nL 78.082931 341.357324 \r\nL 78.191487 341.047425 \r\nL 78.218626 340.938048 \r\nL 78.318135 340.537002 \r\nL 78.345274 340.427626 \r\nL 78.435737 340.172414 \r\nL 78.517154 340.063038 \r\nL 78.612141 339.807827 \r\nL 78.666419 339.698451 \r\nL 78.765928 339.443239 \r\nL 78.81116 339.333863 \r\nL 78.919716 339.078652 \r\nL 79.023749 338.987505 \r\nL 79.132305 338.604688 \r\nL 79.182059 338.513541 \r\nL 79.290615 338.185412 \r\nL 79.349416 338.094266 \r\nL 79.43988 337.875513 \r\nL 79.507727 337.784366 \r\nL 79.616283 337.401549 \r\nL 79.679607 337.292173 \r\nL 79.788163 337.055191 \r\nL 79.837918 336.964044 \r\nL 79.941951 336.708833 \r\nL 80.005275 336.599457 \r\nL 80.109308 336.398934 \r\nL 80.195248 336.289557 \r\nL 80.285711 335.997887 \r\nL 80.358082 335.92497 \r\nL 80.462114 335.779135 \r\nL 80.502823 335.669759 \r\nL 80.611379 335.3234 \r\nL 80.661134 335.214024 \r\nL 80.765166 334.831207 \r\nL 80.828491 334.721831 \r\nL 80.937047 334.46662 \r\nL 81.059172 334.357243 \r\nL 81.154158 333.992656 \r\nL 81.249145 333.88328 \r\nL 81.353178 333.664527 \r\nL 81.479826 333.555151 \r\nL 81.579336 333.227022 \r\nL 81.633614 333.117646 \r\nL 81.724077 332.825976 \r\nL 81.787401 332.7166 \r\nL 81.895957 332.297324 \r\nL 81.959281 332.187948 \r\nL 82.063314 331.987425 \r\nL 82.122115 331.878048 \r\nL 82.230671 331.641066 \r\nL 82.280426 331.568149 \r\nL 82.375412 331.203561 \r\nL 82.434214 331.130644 \r\nL 82.533723 330.711368 \r\nL 82.606094 330.601992 \r\nL 82.71465 330.310322 \r\nL 82.759881 330.219175 \r\nL 82.836775 329.836358 \r\nL 82.931761 329.726982 \r\nL 83.035794 329.49 \r\nL 83.085549 329.380624 \r\nL 83.194105 328.815513 \r\nL 83.225767 328.706137 \r\nL 83.334323 328.487384 \r\nL 83.388601 328.396237 \r\nL 83.492634 328.177485 \r\nL 83.578574 328.086338 \r\nL 83.682606 327.849356 \r\nL 83.732361 327.758209 \r\nL 83.813778 327.393622 \r\nL 83.999228 327.284245 \r\nL 84.107784 326.901429 \r\nL 84.184678 326.810282 \r\nL 84.293233 326.664447 \r\nL 84.347511 326.55507 \r\nL 84.451544 326.208712 \r\nL 84.528438 326.099336 \r\nL 84.605332 325.935272 \r\nL 84.713888 325.825895 \r\nL 84.808874 325.68006 \r\nL 84.849583 325.607143 \r\nL 84.958138 325.370161 \r\nL 84.994324 325.297243 \r\nL 85.098357 325.023803 \r\nL 85.134542 324.950885 \r\nL 85.243098 324.258169 \r\nL 85.315468 324.148793 \r\nL 85.414978 323.838893 \r\nL 85.473779 323.729517 \r\nL 85.582335 323.601911 \r\nL 85.613997 323.492535 \r\nL 85.722553 323.255553 \r\nL 85.785877 323.164406 \r\nL 85.894433 322.76336 \r\nL 85.917049 322.690443 \r\nL 86.025605 322.271167 \r\nL 86.079883 322.18002 \r\nL 86.188439 321.578451 \r\nL 86.220101 321.469074 \r\nL 86.328657 321.30501 \r\nL 86.405551 321.195634 \r\nL 86.496014 321.031569 \r\nL 86.545769 320.940423 \r\nL 86.654325 320.594064 \r\nL 86.749311 320.484688 \r\nL 86.844297 320.174789 \r\nL 86.957376 320.065412 \r\nL 87.065932 319.883119 \r\nL 87.129257 319.773742 \r\nL 87.237813 319.390926 \r\nL 87.337322 319.299779 \r\nL 87.427785 319.008109 \r\nL 87.554434 318.898732 \r\nL 87.66299 318.716439 \r\nL 87.74893 318.625292 \r\nL 87.852963 318.351851 \r\nL 87.889148 318.242475 \r\nL 87.993181 318.005493 \r\nL 88.029366 317.914346 \r\nL 88.137922 317.659135 \r\nL 88.165061 317.549759 \r\nL 88.269094 317.312777 \r\nL 88.314325 317.22163 \r\nL 88.422881 316.966419 \r\nL 88.477159 316.857042 \r\nL 88.585715 316.583602 \r\nL 88.630947 316.474225 \r\nL 88.730456 316.200785 \r\nL 88.784734 316.127867 \r\nL 88.870674 315.872656 \r\nL 88.947568 315.781509 \r\nL 89.051601 315.544527 \r\nL 89.137541 315.435151 \r\nL 89.237051 315.015875 \r\nL 89.345607 314.906499 \r\nL 89.440593 314.523682 \r\nL 89.544626 314.414306 \r\nL 89.644135 314.177324 \r\nL 89.698413 314.086177 \r\nL 89.806969 313.758048 \r\nL 89.870293 313.666901 \r\nL 89.974326 313.320543 \r\nL 90.024081 313.229396 \r\nL 90.128114 312.773662 \r\nL 90.191438 312.700744 \r\nL 90.299994 312.336157 \r\nL 90.358795 312.226781 \r\nL 90.449258 312.026258 \r\nL 90.503536 311.935111 \r\nL 90.607569 311.734588 \r\nL 90.648277 311.625211 \r\nL 90.75231 311.297082 \r\nL 90.793019 311.224165 \r\nL 90.892528 310.968954 \r\nL 90.969422 310.859577 \r\nL 91.073455 310.567907 \r\nL 91.141302 310.458531 \r\nL 91.245335 310.294467 \r\nL 91.308659 310.185091 \r\nL 91.412692 309.929879 \r\nL 91.462447 309.838732 \r\nL 91.561956 309.492374 \r\nL 91.742883 309.382998 \r\nL 91.851439 309.146016 \r\nL 91.982611 309.03664 \r\nL 92.091166 308.836117 \r\nL 92.186153 308.72674 \r\nL 92.285662 308.507988 \r\nL 92.33994 308.398612 \r\nL 92.43945 308.307465 \r\nL 92.516344 308.198089 \r\nL 92.620377 307.924648 \r\nL 92.665608 307.815272 \r\nL 92.774164 307.651207 \r\nL 92.846535 307.541831 \r\nL 92.941521 307.377767 \r\nL 93.018415 307.26839 \r\nL 93.126971 306.812656 \r\nL 93.181249 306.70328 \r\nL 93.289805 306.502757 \r\nL 93.339559 306.41161 \r\nL 93.434546 306.174628 \r\nL 93.525009 306.065252 \r\nL 93.615472 305.955875 \r\nL 93.66975 305.846499 \r\nL 93.778306 305.664205 \r\nL 93.832584 305.591288 \r\nL 93.94114 305.390765 \r\nL 93.968279 305.299618 \r\nL 94.067789 305.135553 \r\nL 94.167298 305.026177 \r\nL 94.275854 304.716278 \r\nL 94.348225 304.606901 \r\nL 94.456781 304.36992 \r\nL 94.547244 304.260543 \r\nL 94.628661 304.041791 \r\nL 94.682939 303.932414 \r\nL 94.777925 303.677203 \r\nL 94.863865 303.586056 \r\nL 94.967898 303.312616 \r\nL 95.067408 303.203239 \r\nL 95.175964 303.002716 \r\nL 95.293566 302.89334 \r\nL 95.397599 302.583441 \r\nL 95.497108 302.474064 \r\nL 95.592095 302.145936 \r\nL 95.678035 302.036559 \r\nL 95.786591 301.890724 \r\nL 95.858961 301.781348 \r\nL 95.953948 301.489678 \r\nL 96.035365 301.380302 \r\nL 96.14392 301.015714 \r\nL 96.220814 300.906338 \r\nL 96.306754 300.760503 \r\nL 96.383648 300.651127 \r\nL 96.492204 300.450604 \r\nL 96.591714 300.341227 \r\nL 96.70027 300.158934 \r\nL 96.754547 300.049557 \r\nL 96.863103 299.794346 \r\nL 96.930951 299.703199 \r\nL 97.039507 299.411529 \r\nL 97.093785 299.320382 \r\nL 97.179725 299.119859 \r\nL 97.261142 299.028712 \r\nL 97.365174 298.79173 \r\nL 97.414929 298.682354 \r\nL 97.518962 298.372455 \r\nL 97.641087 298.263078 \r\nL 97.736074 298.044326 \r\nL 97.808444 297.93495 \r\nL 97.903431 297.770885 \r\nL 98.011987 297.661509 \r\nL 98.11602 297.424527 \r\nL 98.18839 297.315151 \r\nL 98.260761 297.169316 \r\nL 98.337655 297.05994 \r\nL 98.437164 296.877646 \r\nL 98.505012 296.786499 \r\nL 98.613567 296.403682 \r\nL 98.699508 296.294306 \r\nL 98.80354 296.1667 \r\nL 98.934712 296.057324 \r\nL 99.034222 295.729195 \r\nL 99.0885 295.619819 \r\nL 99.192532 295.346378 \r\nL 99.233241 295.237002 \r\nL 99.33275 295.018249 \r\nL 99.387028 294.908873 \r\nL 99.495584 294.653662 \r\nL 99.549862 294.544286 \r\nL 99.658418 294.398451 \r\nL 99.717219 294.289074 \r\nL 99.785067 294.088551 \r\nL 99.916238 293.997404 \r\nL 100.011225 293.760423 \r\nL 100.079072 293.669276 \r\nL 100.187628 293.377606 \r\nL 100.223813 293.268229 \r\nL 100.282615 293.104165 \r\nL 100.386647 293.031247 \r\nL 100.495203 292.721348 \r\nL 100.567574 292.611972 \r\nL 100.630898 292.411449 \r\nL 100.734931 292.320302 \r\nL 100.843487 292.08332 \r\nL 100.915857 291.992173 \r\nL 101.01989 291.79165 \r\nL 101.078691 291.682274 \r\nL 101.178201 291.49998 \r\nL 101.223432 291.445292 \r\nL 101.322942 291.153622 \r\nL 101.46316 291.044245 \r\nL 101.571716 290.861952 \r\nL 101.630517 290.752575 \r\nL 101.73455 290.497364 \r\nL 101.829536 290.387988 \r\nL 101.938092 290.169235 \r\nL 102.09188 290.059859 \r\nL 102.200436 289.804648 \r\nL 102.259237 289.695272 \r\nL 102.331607 289.531207 \r\nL 102.399455 289.44006 \r\nL 102.508011 289.111932 \r\nL 102.562289 289.002555 \r\nL 102.670845 288.838491 \r\nL 102.820109 288.729115 \r\nL 102.919619 288.56505 \r\nL 103.005559 288.473903 \r\nL 103.114115 288.164004 \r\nL 103.163869 288.072857 \r\nL 103.263379 287.744728 \r\nL 103.349319 287.653581 \r\nL 103.457875 287.343682 \r\nL 103.552861 287.234306 \r\nL 103.652371 287.015553 \r\nL 103.720218 286.906177 \r\nL 103.819728 286.650966 \r\nL 103.914714 286.54159 \r\nL 104.014224 286.23169 \r\nL 104.091118 286.140543 \r\nL 104.199674 285.885332 \r\nL 104.272044 285.775956 \r\nL 104.367031 285.593662 \r\nL 104.412262 285.502515 \r\nL 104.520818 285.247304 \r\nL 104.620328 285.137928 \r\nL 104.724361 284.973863 \r\nL 104.828393 284.864487 \r\nL 104.936949 284.645734 \r\nL 105.018366 284.554588 \r\nL 105.117876 284.354064 \r\nL 105.203816 284.244688 \r\nL 105.312372 283.880101 \r\nL 105.389266 283.788954 \r\nL 105.479729 283.679577 \r\nL 105.547576 283.60666 \r\nL 105.651609 283.242072 \r\nL 105.71041 283.132696 \r\nL 105.80992 282.932173 \r\nL 105.859675 282.859256 \r\nL 105.963707 282.476439 \r\nL 106.031555 282.385292 \r\nL 106.135587 282.093622 \r\nL 106.16725 281.984245 \r\nL 106.271282 281.85664 \r\nL 106.361746 281.747264 \r\nL 106.452209 281.528511 \r\nL 106.560765 281.437364 \r\nL 106.642182 281.236841 \r\nL 106.827631 281.127465 \r\nL 106.936187 280.799336 \r\nL 107.022127 280.708189 \r\nL 107.130683 280.434748 \r\nL 107.157822 280.325372 \r\nL 107.234716 280.033702 \r\nL 107.329703 279.924326 \r\nL 107.429212 279.705573 \r\nL 107.492536 279.596197 \r\nL 107.601092 279.432133 \r\nL 107.718695 279.322757 \r\nL 107.82725 279.195151 \r\nL 107.867959 279.085775 \r\nL 107.971992 278.958169 \r\nL 108.053409 278.848793 \r\nL 108.139349 278.684728 \r\nL 108.234335 278.593581 \r\nL 108.329322 278.411288 \r\nL 108.415262 278.301911 \r\nL 108.523818 278.137847 \r\nL 108.573572 278.028471 \r\nL 108.682128 277.700342 \r\nL 108.71379 277.590966 \r\nL 108.79973 277.299296 \r\nL 108.876624 277.18992 \r\nL 108.976134 277.007626 \r\nL 109.021365 276.898249 \r\nL 109.125398 276.661268 \r\nL 109.265616 276.551891 \r\nL 109.365126 276.351368 \r\nL 109.42845 276.241992 \r\nL 109.537006 275.913863 \r\nL 109.595807 275.804487 \r\nL 109.704363 275.640423 \r\nL 109.790303 275.531046 \r\nL 109.894336 275.42167 \r\nL 110.0436 275.312294 \r\nL 110.138587 275.111771 \r\nL 110.161203 275.020624 \r\nL 110.269758 274.820101 \r\nL 110.364745 274.710724 \r\nL 110.396407 274.510201 \r\nL 110.518532 274.400825 \r\nL 110.627088 274.072696 \r\nL 110.681366 273.96332 \r\nL 110.785399 273.799256 \r\nL 110.871339 273.689879 \r\nL 110.979895 273.361751 \r\nL 111.052266 273.270604 \r\nL 111.156298 273.015392 \r\nL 111.20153 272.906016 \r\nL 111.305563 272.77841 \r\nL 111.37341 272.669034 \r\nL 111.481966 272.304447 \r\nL 111.531721 272.19507 \r\nL 111.63123 271.9034 \r\nL 111.735263 271.794024 \r\nL 111.843819 271.557042 \r\nL 111.952375 271.447666 \r\nL 112.056408 271.210684 \r\nL 112.164964 271.101308 \r\nL 112.27352 270.864326 \r\nL 112.323274 270.773179 \r\nL 112.43183 270.536197 \r\nL 112.563002 270.44505 \r\nL 112.662512 270.226298 \r\nL 112.752975 270.116922 \r\nL 112.829869 269.934628 \r\nL 112.979133 269.825252 \r\nL 113.078643 269.661187 \r\nL 113.169106 269.551811 \r\nL 113.277662 269.187223 \r\nL 113.322893 269.150765 \r\nL 113.426926 268.822636 \r\nL 113.50382 268.731489 \r\nL 113.612376 268.549195 \r\nL 113.653084 268.439819 \r\nL 113.757117 268.312213 \r\nL 113.820441 268.202837 \r\nL 113.906381 268.057002 \r\nL 113.974229 267.947626 \r\nL 114.078262 267.783561 \r\nL 114.150632 267.747103 \r\nL 114.259188 267.491891 \r\nL 114.340605 267.382515 \r\nL 114.444638 267.145533 \r\nL 114.539624 267.054386 \r\nL 114.639134 266.853863 \r\nL 114.774829 266.744487 \r\nL 114.878862 266.562193 \r\nL 114.946709 266.452817 \r\nL 115.046219 266.270523 \r\nL 115.136682 266.161147 \r\nL 115.236191 265.905936 \r\nL 115.358317 265.796559 \r\nL 115.466873 265.504889 \r\nL 115.539243 265.395513 \r\nL 115.647799 265.140302 \r\nL 115.729216 265.030926 \r\nL 115.824203 264.793944 \r\nL 115.910143 264.702797 \r\nL 116.005129 264.502274 \r\nL 116.086546 264.392897 \r\nL 116.190579 264.192374 \r\nL 116.267473 264.101227 \r\nL 116.366982 263.900704 \r\nL 116.430306 263.791328 \r\nL 116.52077 263.627264 \r\nL 116.615756 263.554346 \r\nL 116.719789 263.280905 \r\nL 116.787636 263.171529 \r\nL 116.896192 262.879859 \r\nL 117.018318 262.770483 \r\nL 117.126874 262.369437 \r\nL 117.172105 262.27829 \r\nL 117.280661 262.059537 \r\nL 117.371124 261.96839 \r\nL 117.457064 261.67672 \r\nL 117.633468 261.567344 \r\nL 117.732977 261.38505 \r\nL 117.827964 261.330362 \r\nL 117.93652 261.075151 \r\nL 117.995321 260.965775 \r\nL 118.103877 260.747022 \r\nL 118.153632 260.637646 \r\nL 118.198863 260.564728 \r\nL 118.307419 260.455352 \r\nL 118.402405 260.291288 \r\nL 118.569762 260.181911 \r\nL 118.678318 260.036076 \r\nL 118.755212 259.94493 \r\nL 118.863768 259.726177 \r\nL 119.008509 259.616801 \r\nL 119.117065 259.379819 \r\nL 119.248237 259.270443 \r\nL 119.334177 259.05169 \r\nL 119.433687 258.942314 \r\nL 119.537719 258.577726 \r\nL 119.623659 258.46835 \r\nL 119.718646 258.304286 \r\nL 119.772924 258.194909 \r\nL 119.876957 258.030845 \r\nL 119.913142 257.921469 \r\nL 119.980989 257.739175 \r\nL 120.075976 257.648028 \r\nL 120.157393 257.374588 \r\nL 120.274995 257.265211 \r\nL 120.351889 257.228753 \r\nL 120.474014 257.119376 \r\nL 120.58257 256.864165 \r\nL 120.650417 256.773018 \r\nL 120.75445 256.42666 \r\nL 120.84039 256.317284 \r\nL 120.948946 256.098531 \r\nL 121.02584 255.989155 \r\nL 121.120826 255.84332 \r\nL 121.292707 255.733944 \r\nL 121.3696 255.55165 \r\nL 121.464587 255.442274 \r\nL 121.559573 255.296439 \r\nL 121.659083 255.187062 \r\nL 121.767639 254.986539 \r\nL 121.830963 254.877163 \r\nL 121.939519 254.694869 \r\nL 122.034505 254.585493 \r\nL 122.115922 254.348511 \r\nL 122.215432 254.239135 \r\nL 122.305895 253.947465 \r\nL 122.428021 253.838089 \r\nL 122.513961 253.546419 \r\nL 122.604424 253.473501 \r\nL 122.681318 253.327666 \r\nL 122.78535 253.236519 \r\nL 122.889383 253.017767 \r\nL 122.997939 252.92662 \r\nL 123.097449 252.63495 \r\nL 123.192435 252.525573 \r\nL 123.273852 252.379738 \r\nL 123.350746 252.32505 \r\nL 123.459302 252.069839 \r\nL 123.554288 251.960463 \r\nL 123.662844 251.796398 \r\nL 123.748784 251.723481 \r\nL 123.839247 251.431811 \r\nL 123.979465 251.322435 \r\nL 124.074452 251.085453 \r\nL 124.173961 250.994306 \r\nL 124.273471 250.720865 \r\nL 124.341318 250.647948 \r\nL 124.436305 250.447425 \r\nL 124.55843 250.338048 \r\nL 124.630801 250.265131 \r\nL 124.734834 250.192213 \r\nL 124.820774 250.046378 \r\nL 124.933853 249.955231 \r\nL 125.037886 249.754708 \r\nL 125.146441 249.663561 \r\nL 125.223335 249.535956 \r\nL 125.318322 249.444809 \r\nL 125.377123 249.317203 \r\nL 125.499248 249.207827 \r\nL 125.553526 249.043763 \r\nL 125.71636 248.934386 \r\nL 125.824916 248.770322 \r\nL 125.879194 248.660946 \r\nL 125.983227 248.53334 \r\nL 126.037505 248.423964 \r\nL 126.14606 248.24167 \r\nL 126.191292 248.132294 \r\nL 126.250093 248.004688 \r\nL 126.358649 247.895312 \r\nL 126.462682 247.731247 \r\nL 126.661701 247.621871 \r\nL 126.770257 247.494266 \r\nL 126.887859 247.384889 \r\nL 126.978322 247.293742 \r\nL 127.109494 247.184366 \r\nL 127.21805 247.002072 \r\nL 127.30399 246.892696 \r\nL 127.4035 246.728632 \r\nL 127.462301 246.637485 \r\nL 127.516579 246.509879 \r\nL 127.634181 246.400503 \r\nL 127.742737 246.236439 \r\nL 127.819631 246.127062 \r\nL 127.914617 245.853622 \r\nL 127.996034 245.744245 \r\nL 128.091021 245.580181 \r\nL 128.186007 245.470805 \r\nL 128.294563 245.397887 \r\nL 128.348841 245.288511 \r\nL 128.457397 244.996841 \r\nL 128.511675 244.887465 \r\nL 128.620231 244.668712 \r\nL 128.688078 244.577565 \r\nL 128.796634 244.322354 \r\nL 128.850912 244.231207 \r\nL 128.959468 244.085372 \r\nL 129.086116 243.975996 \r\nL 129.181103 243.830161 \r\nL 129.294182 243.739014 \r\nL 129.398215 243.55672 \r\nL 129.470585 243.465573 \r\nL 129.574618 243.28328 \r\nL 129.637942 243.192133 \r\nL 129.746498 242.936922 \r\nL 129.846008 242.827545 \r\nL 129.954564 242.68171 \r\nL 130.045027 242.590563 \r\nL 130.153583 242.40827 \r\nL 130.185245 242.371811 \r\nL 130.253092 242.134829 \r\nL 130.311894 242.025453 \r\nL 130.411403 241.879618 \r\nL 130.49282 241.788471 \r\nL 130.601376 241.496801 \r\nL 130.687316 241.387425 \r\nL 130.791349 241.132213 \r\nL 130.841104 241.041066 \r\nL 130.913474 240.858773 \r\nL 131.157725 240.749396 \r\nL 131.252711 240.475956 \r\nL 131.329605 240.366579 \r\nL 131.424592 240.184286 \r\nL 131.619088 240.074909 \r\nL 131.72312 239.874386 \r\nL 131.836199 239.76501 \r\nL 131.944755 239.528028 \r\nL 132.00808 239.418652 \r\nL 132.116636 239.163441 \r\nL 132.17996 239.072294 \r\nL 132.256854 238.89 \r\nL 132.374456 238.798853 \r\nL 132.483012 238.616559 \r\nL 132.550859 238.507183 \r\nL 132.659415 238.343119 \r\nL 132.731786 238.233742 \r\nL 132.831295 237.942072 \r\nL 132.935328 237.832696 \r\nL 133.043884 237.650402 \r\nL 133.184102 237.541026 \r\nL 133.260996 237.395191 \r\nL 133.428353 237.285815 \r\nL 133.527862 237.194668 \r\nL 133.58214 237.103521 \r\nL 133.690696 236.884769 \r\nL 133.776636 236.793622 \r\nL 133.885192 236.410805 \r\nL 133.948517 236.301429 \r\nL 134.052549 236.192052 \r\nL 134.147536 236.082676 \r\nL 134.242522 235.991529 \r\nL 134.287754 235.918612 \r\nL 134.39631 235.68163 \r\nL 134.459634 235.572254 \r\nL 134.56819 235.408189 \r\nL 134.694838 235.298813 \r\nL 134.803394 235.116519 \r\nL 134.857672 235.007143 \r\nL 134.961705 234.770161 \r\nL 135.034076 234.715473 \r\nL 135.133585 234.51495 \r\nL 135.233095 234.405573 \r\nL 135.337128 234.186821 \r\nL 135.459253 234.077445 \r\nL 135.549716 233.91338 \r\nL 135.676365 233.804004 \r\nL 135.739689 233.712857 \r\nL 135.816583 233.603481 \r\nL 135.920616 233.402958 \r\nL 136.006556 233.293581 \r\nL 136.110588 233.020141 \r\nL 136.232714 232.910765 \r\nL 136.34127 232.76493 \r\nL 136.395548 232.673783 \r\nL 136.454349 232.436801 \r\nL 136.594567 232.327425 \r\nL 136.666938 232.218048 \r\nL 136.838818 232.108672 \r\nL 136.929281 232.017525 \r\nL 137.119254 231.908149 \r\nL 137.223287 231.798773 \r\nL 137.349935 231.689396 \r\nL 137.453968 231.397726 \r\nL 137.508246 231.28835 \r\nL 137.594186 231.178974 \r\nL 137.693696 231.069598 \r\nL 137.784159 230.960221 \r\nL 137.888192 230.850845 \r\nL 137.987701 230.632093 \r\nL 138.136966 230.522716 \r\nL 138.245521 230.267505 \r\nL 138.349554 230.158129 \r\nL 138.45811 229.939376 \r\nL 138.535004 229.848229 \r\nL 138.64356 229.684165 \r\nL 138.7295 229.574789 \r\nL 138.829009 229.410724 \r\nL 138.937565 229.301348 \r\nL 139.023505 229.24666 \r\nL 139.17277 229.137284 \r\nL 139.231571 229.046137 \r\nL 139.371789 228.936761 \r\nL 139.480345 228.699779 \r\nL 139.557239 228.590402 \r\nL 139.638656 228.499256 \r\nL 139.729119 228.408109 \r\nL 139.833152 228.262274 \r\nL 139.900999 228.152897 \r\nL 140.009555 228.007062 \r\nL 140.077402 227.897686 \r\nL 140.185958 227.624245 \r\nL 140.285468 227.514869 \r\nL 140.375931 227.350805 \r\nL 140.479964 227.259658 \r\nL 140.565904 227.132052 \r\nL 140.683506 227.022676 \r\nL 140.787539 226.89507 \r\nL 140.864433 226.785694 \r\nL 140.968466 226.658089 \r\nL 141.063452 226.566942 \r\nL 141.158438 226.457565 \r\nL 141.285087 226.366419 \r\nL 141.393643 226.220584 \r\nL 141.46149 226.111207 \r\nL 141.565523 225.928913 \r\nL 141.692172 225.819537 \r\nL 141.800728 225.673702 \r\nL 141.841436 225.564326 \r\nL 141.936422 225.43672 \r\nL 142.07664 225.327344 \r\nL 142.167104 225.217968 \r\nL 142.384216 225.14505 \r\nL 142.470156 224.962757 \r\nL 142.610374 224.85338 \r\nL 142.714406 224.671087 \r\nL 142.773208 224.56171 \r\nL 142.854624 224.452334 \r\nL 142.994843 224.342958 \r\nL 143.098875 224.251811 \r\nL 143.175769 224.142435 \r\nL 143.266232 223.759618 \r\nL 143.379311 223.650241 \r\nL 143.478821 223.577324 \r\nL 143.587377 223.467948 \r\nL 143.695933 223.212736 \r\nL 143.76378 223.10336 \r\nL 143.86329 222.939296 \r\nL 143.94923 222.848149 \r\nL 144.030647 222.738773 \r\nL 144.13468 222.647626 \r\nL 144.238712 222.52002 \r\nL 144.460347 222.410644 \r\nL 144.559857 222.246579 \r\nL 144.668413 222.137203 \r\nL 144.772446 221.973139 \r\nL 144.853863 221.863763 \r\nL 144.962418 221.663239 \r\nL 145.00765 221.572093 \r\nL 145.09359 221.444487 \r\nL 145.26547 221.35334 \r\nL 145.355934 221.207505 \r\nL 145.419258 221.098129 \r\nL 145.527814 220.952294 \r\nL 145.690648 220.861147 \r\nL 145.799204 220.624165 \r\nL 145.939422 220.514789 \r\nL 146.047978 220.314266 \r\nL 146.093209 220.204889 \r\nL 146.188196 219.913219 \r\nL 146.391738 219.803843 \r\nL 146.486724 219.60332 \r\nL 146.577188 219.493944 \r\nL 146.685744 219.384567 \r\nL 146.803346 219.275191 \r\nL 146.889286 219.111127 \r\nL 147.006888 219.001751 \r\nL 147.088305 218.855915 \r\nL 147.151629 218.746539 \r\nL 147.246616 218.618934 \r\nL 147.332556 218.546016 \r\nL 147.441112 218.290805 \r\nL 147.549668 218.199658 \r\nL 147.649177 217.816841 \r\nL 147.807488 217.707465 \r\nL 147.911521 217.5434 \r\nL 148.029123 217.452254 \r\nL 148.115063 217.26996 \r\nL 148.268851 217.160584 \r\nL 148.350267 217.014748 \r\nL 148.436208 216.96006 \r\nL 148.531194 216.795996 \r\nL 148.589995 216.68662 \r\nL 148.689505 216.37672 \r\nL 148.793537 216.285573 \r\nL 148.879478 216.10328 \r\nL 148.974464 215.993903 \r\nL 149.037788 215.884527 \r\nL 149.209668 215.79338 \r\nL 149.295609 215.702233 \r\nL 149.395118 215.611087 \r\nL 149.503674 215.374105 \r\nL 149.585091 215.264728 \r\nL 149.693647 215.155352 \r\nL 149.775064 215.045976 \r\nL 149.879097 214.91837 \r\nL 150.010268 214.808994 \r\nL 150.114301 214.681388 \r\nL 150.195718 214.572012 \r\nL 150.245473 214.407948 \r\nL 150.408307 214.298571 \r\nL 150.507816 214.152736 \r\nL 150.553048 214.04336 \r\nL 150.657081 213.897525 \r\nL 150.761113 213.788149 \r\nL 150.838007 213.642314 \r\nL 150.901331 213.532938 \r\nL 151.005364 213.441791 \r\nL 151.077735 213.332414 \r\nL 151.136536 213.259497 \r\nL 151.29937 213.150121 \r\nL 151.398879 212.894909 \r\nL 151.543621 212.785533 \r\nL 151.611468 212.639698 \r\nL 151.805964 212.530322 \r\nL 151.91452 212.366258 \r\nL 152.004983 212.256881 \r\nL 152.0864 212.111046 \r\nL 152.326128 212.00167 \r\nL 152.43016 211.874064 \r\nL 152.534193 211.764688 \r\nL 152.62918 211.564165 \r\nL 152.796537 211.454789 \r\nL 152.905093 211.217807 \r\nL 153.05888 211.108431 \r\nL 153.162913 210.926137 \r\nL 153.248853 210.816761 \r\nL 153.357409 210.725614 \r\nL 153.547382 210.616237 \r\nL 153.646891 210.488632 \r\nL 153.769017 210.415714 \r\nL 153.877573 210.215191 \r\nL 153.990652 210.105815 \r\nL 154.090161 209.905292 \r\nL 154.185148 209.795915 \r\nL 154.234903 209.686539 \r\nL 154.357028 209.577163 \r\nL 154.461061 209.467787 \r\nL 154.601279 209.35841 \r\nL 154.696265 209.267264 \r\nL 154.795775 209.157887 \r\nL 154.899807 208.939135 \r\nL 154.985748 208.829759 \r\nL 155.085257 208.683924 \r\nL 155.27523 208.574547 \r\nL 155.365693 208.374024 \r\nL 155.514958 208.264648 \r\nL 155.600898 208.082354 \r\nL 155.713977 207.972978 \r\nL 155.808963 207.790684 \r\nL 155.885857 207.699537 \r\nL 155.949181 207.553702 \r\nL 156.026075 207.499014 \r\nL 156.066784 207.407867 \r\nL 156.193432 207.298491 \r\nL 156.297465 207.04328 \r\nL 156.415067 206.952133 \r\nL 156.510053 206.769839 \r\nL 156.718119 206.660463 \r\nL 156.826675 206.496398 \r\nL 156.894522 206.387022 \r\nL 156.998555 206.259416 \r\nL 157.089018 206.15004 \r\nL 157.184005 206.004205 \r\nL 157.324223 205.894829 \r\nL 157.423732 205.712535 \r\nL 157.545858 205.603159 \r\nL 157.649891 205.457324 \r\nL 157.776539 205.347948 \r\nL 157.871526 205.220342 \r\nL 158.02079 205.129195 \r\nL 158.129346 204.98336 \r\nL 158.269564 204.873984 \r\nL 158.332888 204.673461 \r\nL 158.45049 204.618773 \r\nL 158.554523 204.40002 \r\nL 158.708311 204.290644 \r\nL 158.80782 204.144809 \r\nL 158.957085 204.035433 \r\nL 159.033978 203.907827 \r\nL 159.151581 203.834909 \r\nL 159.255613 203.652616 \r\nL 159.359646 203.543239 \r\nL 159.418447 203.506781 \r\nL 159.603897 203.397404 \r\nL 159.703407 203.196881 \r\nL 159.789347 203.087505 \r\nL 159.861717 202.868753 \r\nL 159.943134 202.759376 \r\nL 159.96575 202.704688 \r\nL 160.13763 202.595312 \r\nL 160.214524 202.449477 \r\nL 160.304987 202.376559 \r\nL 160.404497 202.176036 \r\nL 160.449728 202.084889 \r\nL 160.558284 201.975513 \r\nL 160.589947 201.902596 \r\nL 160.689456 201.793219 \r\nL 160.75278 201.683843 \r\nL 160.834197 201.501549 \r\nL 160.956323 201.392173 \r\nL 161.064879 201.173421 \r\nL 161.141772 201.064044 \r\nL 161.223189 200.89998 \r\nL 161.286514 200.808833 \r\nL 161.336268 200.735915 \r\nL 161.494579 200.626539 \r\nL 161.575996 200.407787 \r\nL 161.72526 200.29841 \r\nL 161.833816 200.207264 \r\nL 161.897141 200.097887 \r\nL 161.99665 199.933823 \r\nL 162.073544 199.860905 \r\nL 162.141391 199.696841 \r\nL 162.277086 199.587465 \r\nL 162.381119 199.478089 \r\nL 162.52586 199.368712 \r\nL 162.629893 199.241107 \r\nL 162.779157 199.14996 \r\nL 162.878667 198.985895 \r\nL 162.973653 198.876519 \r\nL 163.064117 198.730684 \r\nL 163.204335 198.621308 \r\nL 163.312891 198.457243 \r\nL 163.444062 198.347867 \r\nL 163.525479 198.165573 \r\nL 163.729022 198.056197 \r\nL 163.7833 197.928592 \r\nL 163.995888 197.819215 \r\nL 164.104444 197.655151 \r\nL 164.244662 197.545775 \r\nL 164.348695 197.39994 \r\nL 164.48439 197.290563 \r\nL 164.57033 197.162958 \r\nL 164.746733 197.053581 \r\nL 164.846243 196.925976 \r\nL 164.990984 196.8166 \r\nL 165.09954 196.688994 \r\nL 165.203573 196.579618 \r\nL 165.312129 196.470241 \r\nL 165.384499 196.360865 \r\nL 165.479486 196.269718 \r\nL 165.583518 196.160342 \r\nL 165.669459 195.978048 \r\nL 165.796107 195.868672 \r\nL 165.904663 195.741066 \r\nL 166.013219 195.63169 \r\nL 166.08559 195.522314 \r\nL 166.275562 195.412938 \r\nL 166.384118 195.248873 \r\nL 166.542429 195.139497 \r\nL 166.650985 195.030121 \r\nL 166.759541 194.920744 \r\nL 166.868097 194.75668 \r\nL 167.039977 194.647304 \r\nL 167.121394 194.592616 \r\nL 167.266135 194.483239 \r\nL 167.370168 194.428551 \r\nL 167.569187 194.319175 \r\nL 167.600849 194.246258 \r\nL 167.795345 194.136881 \r\nL 167.890332 193.826982 \r\nL 168.057689 193.717606 \r\nL 168.10292 193.644688 \r\nL 168.329078 193.535312 \r\nL 168.433111 193.353018 \r\nL 168.573329 193.243642 \r\nL 168.677362 193.116036 \r\nL 168.758779 193.00666 \r\nL 168.862812 192.824366 \r\nL 168.939705 192.71499 \r\nL 169.039215 192.587384 \r\nL 169.116109 192.478008 \r\nL 169.206572 192.277485 \r\nL 169.405591 192.168109 \r\nL 169.505101 192.004044 \r\nL 169.645319 191.912897 \r\nL 169.735782 191.730604 \r\nL 169.898616 191.621227 \r\nL 169.97551 191.420704 \r\nL 170.264992 191.311328 \r\nL 170.373548 191.201952 \r\nL 170.495673 191.092575 \r\nL 170.558998 190.983199 \r\nL 170.685646 190.873823 \r\nL 170.780633 190.709759 \r\nL 170.925374 190.600382 \r\nL 171.015837 190.3634 \r\nL 171.174148 190.272254 \r\nL 171.282704 190.126419 \r\nL 171.431968 190.017042 \r\nL 171.540524 189.925895 \r\nL 171.626464 189.816519 \r\nL 171.689788 189.634225 \r\nL 171.843576 189.561308 \r\nL 171.952132 189.21495 \r\nL 172.142105 189.105573 \r\nL 172.223522 188.90505 \r\nL 172.372786 188.795674 \r\nL 172.440633 188.686298 \r\nL 172.580852 188.576922 \r\nL 172.662268 188.376398 \r\nL 172.811533 188.267022 \r\nL 172.915566 187.993581 \r\nL 173.073876 187.884205 \r\nL 173.182432 187.592535 \r\nL 173.390498 187.483159 \r\nL 173.480961 187.300865 \r\nL 173.562378 187.191489 \r\nL 173.670934 187.009195 \r\nL 173.838291 186.899819 \r\nL 173.842814 186.86336 \r\nL 174.019217 186.753984 \r\nL 174.105157 186.626378 \r\nL 174.245376 186.517002 \r\nL 174.349408 186.352938 \r\nL 174.48058 186.261791 \r\nL 174.575566 186.079497 \r\nL 174.765539 185.970121 \r\nL 174.82434 185.842515 \r\nL 174.937419 185.733139 \r\nL 175.045975 185.587304 \r\nL 175.235948 185.477928 \r\nL 175.326411 185.332093 \r\nL 175.539 185.222716 \r\nL 175.633987 185.058652 \r\nL 175.873714 184.985734 \r\nL 175.977747 184.82167 \r\nL 176.104395 184.712294 \r\nL 176.199382 184.53 \r\nL 176.285322 184.438853 \r\nL 176.371262 184.23833 \r\nL 176.647175 184.128954 \r\nL 176.742161 184.001348 \r\nL 176.877856 183.891972 \r\nL 176.986412 183.727907 \r\nL 177.085922 183.618531 \r\nL 177.194478 183.418008 \r\nL 177.248756 183.308632 \r\nL 177.330173 183.053421 \r\nL 177.48396 182.944044 \r\nL 177.578947 182.798209 \r\nL 177.696549 182.688833 \r\nL 177.705595 182.652374 \r\nL 177.954369 182.542998 \r\nL 178.062925 182.360704 \r\nL 178.148865 182.251328 \r\nL 178.248375 182.141952 \r\nL 178.334315 182.032575 \r\nL 178.402162 181.813823 \r\nL 178.488102 181.704447 \r\nL 178.596658 181.558612 \r\nL 178.745923 181.449235 \r\nL 178.854479 181.339859 \r\nL 178.935896 181.230483 \r\nL 179.035405 181.01173 \r\nL 179.134915 180.902354 \r\nL 179.234424 180.73829 \r\nL 179.315841 180.647143 \r\nL 179.424397 180.483078 \r\nL 179.569138 180.373702 \r\nL 179.659602 180.246097 \r\nL 179.736495 180.13672 \r\nL 179.840528 179.990885 \r\nL 180.093825 179.881509 \r\nL 180.179765 179.735674 \r\nL 180.48734 179.626298 \r\nL 180.550665 179.57161 \r\nL 180.736114 179.462233 \r\nL 180.736114 179.444004 \r\nL 180.948703 179.352857 \r\nL 181.012027 179.225252 \r\nL 181.274371 179.115875 \r\nL 181.382927 178.933581 \r\nL 181.45982 178.842435 \r\nL 181.554807 178.733058 \r\nL 181.780965 178.623682 \r\nL 181.857859 178.496076 \r\nL 181.979984 178.3867 \r\nL 182.070447 178.204406 \r\nL 182.169957 178.09503 \r\nL 182.242328 177.967425 \r\nL 182.337314 177.894507 \r\nL 182.441347 177.675755 \r\nL 182.563472 177.566378 \r\nL 182.658459 177.438773 \r\nL 182.798677 177.347626 \r\nL 182.907233 177.147103 \r\nL 182.961511 177.037726 \r\nL 183.047451 176.92835 \r\nL 183.187669 176.837203 \r\nL 183.287178 176.691368 \r\nL 183.468105 176.581992 \r\nL 183.567614 176.436157 \r\nL 183.76211 176.326781 \r\nL 183.848051 176.199175 \r\nL 183.974699 176.089799 \r\nL 184.083255 175.834588 \r\nL 184.295844 175.725211 \r\nL 184.368214 175.670523 \r\nL 184.571757 175.561147 \r\nL 184.64865 175.488229 \r\nL 184.892901 175.378853 \r\nL 184.996934 175.287706 \r\nL 185.281893 175.17833 \r\nL 185.37688 174.996036 \r\nL 185.54876 174.88666 \r\nL 185.657316 174.704366 \r\nL 185.833719 174.59499 \r\nL 185.933229 174.485614 \r\nL 186.019169 174.376237 \r\nL 186.0644 174.266861 \r\nL 186.227234 174.157485 \r\nL 186.322221 173.902274 \r\nL 186.399114 173.847586 \r\nL 186.503147 173.555915 \r\nL 186.620749 173.446539 \r\nL 186.720259 173.282475 \r\nL 186.860477 173.191328 \r\nL 186.969033 173.100181 \r\nL 187.041404 172.990805 \r\nL 187.140913 172.753823 \r\nL 187.272085 172.644447 \r\nL 187.376118 172.498612 \r\nL 187.516336 172.389235 \r\nL 187.624892 172.26163 \r\nL 187.710832 172.152254 \r\nL 187.810341 172.042877 \r\nL 187.882712 171.933501 \r\nL 187.986745 171.860584 \r\nL 188.02293 171.751207 \r\nL 188.131486 171.66006 \r\nL 188.267181 171.550684 \r\nL 188.357644 171.423078 \r\nL 188.4662 171.313702 \r\nL 188.574756 171.167867 \r\nL 188.687835 171.07672 \r\nL 188.796391 170.949115 \r\nL 188.923039 170.857968 \r\nL 189.027072 170.584527 \r\nL 189.117535 170.475151 \r\nL 189.207999 170.256398 \r\nL 189.348217 170.165252 \r\nL 189.443203 169.964728 \r\nL 189.52462 169.855352 \r\nL 189.628653 169.691288 \r\nL 189.741732 169.581911 \r\nL 189.850288 169.399618 \r\nL 189.940751 169.290241 \r\nL 190.008598 169.107948 \r\nL 190.194048 168.998571 \r\nL 190.298081 168.798048 \r\nL 190.433776 168.688672 \r\nL 190.533285 168.579296 \r\nL 190.605656 168.46992 \r\nL 190.709689 168.324085 \r\nL 190.886092 168.214708 \r\nL 190.944893 168.087103 \r\nL 191.107727 167.977726 \r\nL 191.189144 167.813662 \r\nL 191.288654 167.758974 \r\nL 191.370071 167.649598 \r\nL 191.514812 167.558451 \r\nL 191.614321 167.449074 \r\nL 191.709308 167.357928 \r\nL 191.790725 167.139175 \r\nL 191.903804 167.029799 \r\nL 192.003313 166.938652 \r\nL 192.107346 166.829276 \r\nL 192.215902 166.683441 \r\nL 192.261134 166.592294 \r\nL 192.36969 166.464688 \r\nL 192.518954 166.355312 \r\nL 192.604894 166.245936 \r\nL 192.727019 166.154789 \r\nL 192.835575 165.917807 \r\nL 192.939608 165.808431 \r\nL 193.048164 165.699054 \r\nL 193.14315 165.607907 \r\nL 193.229091 165.498531 \r\nL 193.387401 165.389155 \r\nL 193.464295 165.261549 \r\nL 193.545712 165.152173 \r\nL 193.649745 164.988109 \r\nL 193.780916 164.878732 \r\nL 193.884949 164.805815 \r\nL 194.065876 164.696439 \r\nL 194.133723 164.550604 \r\nL 194.31465 164.441227 \r\nL 194.396067 164.331851 \r\nL 194.495576 164.258934 \r\nL 194.590563 164.003722 \r\nL 194.816721 163.894346 \r\nL 194.911707 163.730282 \r\nL 195.029309 163.620905 \r\nL 195.137865 163.511529 \r\nL 195.20119 163.402153 \r\nL 195.269037 163.256318 \r\nL 195.427348 163.146942 \r\nL 195.504241 162.964648 \r\nL 195.698737 162.855272 \r\nL 195.789201 162.691207 \r\nL 195.906803 162.60006 \r\nL 196.001789 162.417767 \r\nL 196.155577 162.32662 \r\nL 196.264133 162.071408 \r\nL 196.426967 161.962032 \r\nL 196.50386 161.779738 \r\nL 196.68931 161.670362 \r\nL 196.793343 161.524527 \r\nL 196.865714 161.415151 \r\nL 196.9607 161.305775 \r\nL 197.051163 161.196398 \r\nL 197.14615 161.014105 \r\nL 197.31803 160.904728 \r\nL 197.408493 160.740664 \r\nL 197.593943 160.631288 \r\nL 197.693452 160.448994 \r\nL 197.806531 160.357847 \r\nL 197.892472 160.248471 \r\nL 198.096014 160.139095 \r\nL 198.123153 160.029718 \r\nL 198.326695 159.920342 \r\nL 198.426205 159.738048 \r\nL 198.530238 159.628672 \r\nL 198.607131 159.501066 \r\nL 198.742826 159.39169 \r\nL 198.842336 159.264085 \r\nL 199.082063 159.154708 \r\nL 199.154434 159.081791 \r\nL 199.303698 158.972414 \r\nL 199.403208 158.753662 \r\nL 199.489148 158.644286 \r\nL 199.584134 158.425533 \r\nL 199.760538 158.316157 \r\nL 199.851001 158.188551 \r\nL 200.022881 158.079175 \r\nL 200.108821 157.969799 \r\nL 200.344026 157.860423 \r\nL 200.452582 157.714588 \r\nL 200.57923 157.605211 \r\nL 200.660647 157.532294 \r\nL 200.846097 157.422918 \r\nL 200.927514 157.386459 \r\nL 201.131056 157.277082 \r\nL 201.239612 157.113018 \r\nL 201.339122 157.003642 \r\nL 201.402446 156.948954 \r\nL 201.524571 156.839577 \r\nL 201.619558 156.693742 \r\nL 201.75073 156.584366 \r\nL 201.854762 156.493219 \r\nL 202.049258 156.383843 \r\nL 202.153291 156.292696 \r\nL 202.234708 156.18332 \r\nL 202.311602 156.037485 \r\nL 202.456343 155.928109 \r\nL 202.510621 155.818732 \r\nL 202.741302 155.709356 \r\nL 202.822719 155.618209 \r\nL 202.899613 155.545292 \r\nL 203.008169 155.344769 \r\nL 203.076016 155.253622 \r\nL 203.184572 154.961952 \r\nL 203.329313 154.852575 \r\nL 203.437869 154.597364 \r\nL 203.600703 154.506217 \r\nL 203.691166 154.378612 \r\nL 203.790676 154.305694 \r\nL 203.86757 154.196318 \r\nL 204.075635 154.086942 \r\nL 204.161575 153.995795 \r\nL 204.319886 153.886419 \r\nL 204.369641 153.813501 \r\nL 204.532475 153.704125 \r\nL 204.636508 153.594748 \r\nL 204.699832 153.485372 \r\nL 204.776726 153.339537 \r\nL 204.966698 153.230161 \r\nL 205.075254 153.084326 \r\nL 205.215472 152.97495 \r\nL 205.301412 152.829115 \r\nL 205.545663 152.719738 \r\nL 205.649696 152.537445 \r\nL 205.785391 152.446298 \r\nL 205.871331 152.355151 \r\nL 206.007026 152.245775 \r\nL 206.106535 152.09994 \r\nL 206.273893 151.990563 \r\nL 206.34174 151.935875 \r\nL 206.59956 151.844728 \r\nL 206.680977 151.753581 \r\nL 206.848334 151.662435 \r\nL 206.934274 151.534829 \r\nL 207.038307 151.425453 \r\nL 207.083539 151.352535 \r\nL 207.219234 151.243159 \r\nL 207.259942 151.133783 \r\nL 207.436345 151.042636 \r\nL 207.526809 150.878571 \r\nL 207.694166 150.769195 \r\nL 207.802722 150.678048 \r\nL 207.915801 150.605131 \r\nL 208.024357 150.368149 \r\nL 208.218853 150.258773 \r\nL 208.327409 150.076479 \r\nL 208.431441 149.967103 \r\nL 208.535474 149.821268 \r\nL 208.634984 149.711891 \r\nL 208.739016 149.620744 \r\nL 208.811387 149.511368 \r\nL 208.906373 149.401992 \r\nL 209.109916 149.292616 \r\nL 209.141578 149.183239 \r\nL 209.299889 149.092093 \r\nL 209.372259 148.982716 \r\nL 209.467246 148.87334 \r\nL 209.548663 148.691046 \r\nL 209.756728 148.58167 \r\nL 209.860761 148.454064 \r\nL 209.97384 148.362918 \r\nL 210.082396 148.180624 \r\nL 210.150243 148.071247 \r\nL 210.236183 147.907183 \r\nL 210.3176 147.797807 \r\nL 210.421633 147.688431 \r\nL 210.607083 147.579054 \r\nL 210.706592 147.396761 \r\nL 210.955366 147.287384 \r\nL 211.045829 147.232696 \r\nL 211.195094 147.12332 \r\nL 211.299127 146.922797 \r\nL 211.452914 146.813421 \r\nL 211.538854 146.685815 \r\nL 211.642887 146.576439 \r\nL 211.751443 146.430604 \r\nL 211.927846 146.321227 \r\nL 212.022833 146.23008 \r\nL 212.230898 146.120704 \r\nL 212.339454 145.93841 \r\nL 212.43444 145.829034 \r\nL 212.53395 145.756117 \r\nL 212.714877 145.66497 \r\nL 212.809863 145.427988 \r\nL 212.918419 145.336841 \r\nL 213.004359 145.245694 \r\nL 213.167193 145.136318 \r\nL 213.253133 145.045171 \r\nL 213.438583 144.935795 \r\nL 213.50643 144.808189 \r\nL 213.827575 144.698813 \r\nL 213.936131 144.552978 \r\nL 214.03564 144.443602 \r\nL 214.13515 144.352455 \r\nL 214.239183 144.243078 \r\nL 214.329646 144.151932 \r\nL 214.40654 144.042555 \r\nL 214.506049 143.951408 \r\nL 214.582943 143.878491 \r\nL 214.686976 143.677968 \r\nL 214.791008 143.568592 \r\nL 214.890518 143.404527 \r\nL 214.971935 143.31338 \r\nL 215.071444 143.131087 \r\nL 215.356404 143.058169 \r\nL 215.446867 142.802958 \r\nL 215.650409 142.693581 \r\nL 215.754442 142.565976 \r\nL 215.899183 142.4566 \r\nL 215.99417 142.401911 \r\nL 216.161527 142.292535 \r\nL 216.261036 142.16493 \r\nL 216.478148 142.055553 \r\nL 216.582181 141.964406 \r\nL 216.631936 141.87326 \r\nL 216.735968 141.672736 \r\nL 216.894279 141.56336 \r\nL 216.971173 141.417525 \r\nL 217.192808 141.326378 \r\nL 217.287794 141.107626 \r\nL 217.40992 140.998249 \r\nL 217.500383 140.888873 \r\nL 217.789865 140.779497 \r\nL 217.862236 140.670121 \r\nL 218.016024 140.560744 \r\nL 218.124579 140.487827 \r\nL 218.215043 140.378451 \r\nL 218.273844 140.287304 \r\nL 218.409539 140.177928 \r\nL 218.495479 140.068551 \r\nL 218.576896 139.959175 \r\nL 218.676405 139.795111 \r\nL 218.789484 139.703964 \r\nL 218.8121 139.649276 \r\nL 219.16943 139.558129 \r\nL 219.219185 139.430523 \r\nL 219.400111 139.321147 \r\nL 219.481528 139.248229 \r\nL 219.653409 139.138853 \r\nL 219.748395 138.901871 \r\nL 219.893136 138.792495 \r\nL 220.001692 138.64666 \r\nL 220.078586 138.537284 \r\nL 220.160003 138.427907 \r\nL 220.395207 138.318531 \r\nL 220.467578 138.245614 \r\nL 220.639458 138.136237 \r\nL 220.702782 138.06332 \r\nL 220.833954 137.953944 \r\nL 220.924417 137.826338 \r\nL 221.268178 137.716962 \r\nL 221.354118 137.662274 \r\nL 221.548614 137.571127 \r\nL 221.625508 137.461751 \r\nL 221.820004 137.352374 \r\nL 221.896897 137.261227 \r\nL 222.123056 137.151851 \r\nL 222.213519 137.078934 \r\nL 222.471339 136.969557 \r\nL 222.552756 136.841952 \r\nL 222.661312 136.732575 \r\nL 222.769868 136.58674 \r\nL 222.996026 136.477364 \r\nL 223.100059 136.422676 \r\nL 223.375972 136.3133 \r\nL 223.452865 136.240382 \r\nL 223.584037 136.131006 \r\nL 223.692593 135.966942 \r\nL 223.737825 135.857565 \r\nL 223.801149 135.71173 \r\nL 224.036354 135.602354 \r\nL 224.113247 135.401831 \r\nL 224.257988 135.292455 \r\nL 224.362021 135.164849 \r\nL 224.592703 135.055473 \r\nL 224.692212 134.982555 \r\nL 224.787199 134.891408 \r\nL 224.895754 134.782032 \r\nL 225.008834 134.690885 \r\nL 225.09025 134.617968 \r\nL 225.352594 134.508592 \r\nL 225.456627 134.399215 \r\nL 225.619461 134.308068 \r\nL 225.714447 134.107545 \r\nL 225.972267 133.998169 \r\nL 226.058207 133.925252 \r\nL 226.302458 133.815875 \r\nL 226.365782 133.67004 \r\nL 226.537663 133.560664 \r\nL 226.641695 133.487746 \r\nL 226.818099 133.37837 \r\nL 226.926655 133.232535 \r\nL 227.035211 133.123159 \r\nL 227.143766 132.940865 \r\nL 227.356355 132.831489 \r\nL 227.410633 132.722113 \r\nL 227.59156 132.612736 \r\nL 227.691069 132.485131 \r\nL 227.754393 132.393984 \r\nL 227.853903 132.302837 \r\nL 228.071015 132.21169 \r\nL 228.138862 132.138773 \r\nL 228.324312 132.029396 \r\nL 228.428345 131.92002 \r\nL 228.554993 131.828873 \r\nL 228.613794 131.683038 \r\nL 228.830906 131.573662 \r\nL 228.885184 131.518974 \r\nL 229.066111 131.409598 \r\nL 229.066111 131.391368 \r\nL 229.278699 131.281992 \r\nL 229.382732 131.099698 \r\nL 229.577228 131.008551 \r\nL 229.667691 130.953863 \r\nL 229.740062 130.844487 \r\nL 229.835048 130.716881 \r\nL 230.015975 130.607505 \r\nL 230.115485 130.516358 \r\nL 230.32355 130.406982 \r\nL 230.377828 130.334064 \r\nL 230.531616 130.224688 \r\nL 230.640171 130.151771 \r\nL 230.771343 130.042394 \r\nL 230.870853 129.933018 \r\nL 231.033687 129.823642 \r\nL 231.11058 129.677807 \r\nL 231.214613 129.568431 \r\nL 231.318646 129.386137 \r\nL 231.39554 129.29499 \r\nL 231.499572 129.058008 \r\nL 231.680499 128.948632 \r\nL 231.789055 128.821026 \r\nL 231.897611 128.71165 \r\nL 232.006167 128.638732 \r\nL 232.146385 128.547586 \r\nL 232.187093 128.41998 \r\nL 232.36802 128.310604 \r\nL 232.476576 128.219457 \r\nL 232.820336 128.11008 \r\nL 232.906276 128.037163 \r\nL 233.06911 127.927787 \r\nL 233.177666 127.672575 \r\nL 233.272652 127.563199 \r\nL 233.349546 127.435594 \r\nL 233.480718 127.326217 \r\nL 233.553088 127.216841 \r\nL 233.629982 127.107465 \r\nL 233.738538 126.96163 \r\nL 233.95565 126.852254 \r\nL 234.050636 126.761107 \r\nL 234.272271 126.65173 \r\nL 234.326549 126.578813 \r\nL 234.47129 126.469437 \r\nL 234.575323 126.287143 \r\nL 234.787912 126.177767 \r\nL 234.869329 126.050161 \r\nL 235.10001 125.940785 \r\nL 235.204043 125.813179 \r\nL 235.380446 125.703803 \r\nL 235.452817 125.630885 \r\nL 235.620174 125.521509 \r\nL 235.697068 125.448592 \r\nL 235.896087 125.339215 \r\nL 236.004643 125.19338 \r\nL 236.135814 125.084004 \r\nL 236.24437 124.91994 \r\nL 236.407204 124.810563 \r\nL 236.484098 124.719416 \r\nL 236.674071 124.61004 \r\nL 236.719302 124.573581 \r\nL 237.017831 124.464205 \r\nL 237.121864 124.354829 \r\nL 237.357068 124.245453 \r\nL 237.465624 124.081388 \r\nL 237.664644 123.972012 \r\nL 237.755107 123.917324 \r\nL 238.03102 123.826177 \r\nL 238.126006 123.698571 \r\nL 238.410965 123.589195 \r\nL 238.487859 123.498048 \r\nL 238.677832 123.388672 \r\nL 238.772818 123.279296 \r\nL 239.035162 123.16992 \r\nL 239.121102 123.042314 \r\nL 239.256797 122.932938 \r\nL 239.356306 122.823561 \r\nL 239.600557 122.714185 \r\nL 239.668405 122.623038 \r\nL 239.831239 122.513662 \r\nL 239.930748 122.404286 \r\nL 240.04835 122.294909 \r\nL 240.138814 122.203763 \r\nL 240.274509 122.094386 \r\nL 240.360449 121.966781 \r\nL 240.532329 121.857404 \r\nL 240.604699 121.748028 \r\nL 240.880612 121.656881 \r\nL 240.984645 121.438129 \r\nL 241.260558 121.328753 \r\nL 241.296743 121.292294 \r\nL 241.545517 121.201147 \r\nL 241.626934 121.091771 \r\nL 241.721921 120.982394 \r\nL 241.803338 120.891247 \r\nL 242.024973 120.781871 \r\nL 242.09282 120.745412 \r\nL 242.459196 120.636036 \r\nL 242.554183 120.52666 \r\nL 242.789387 120.417284 \r\nL 242.888897 120.271449 \r\nL 243.015545 120.162072 \r\nL 243.119578 120.034467 \r\nL 243.445246 119.925091 \r\nL 243.52214 119.852173 \r\nL 243.716636 119.742797 \r\nL 243.807099 119.578732 \r\nL 243.924701 119.487586 \r\nL 243.997072 119.323521 \r\nL 244.241322 119.214145 \r\nL 244.272985 119.159457 \r\nL 244.476527 119.05008 \r\nL 244.58056 118.940704 \r\nL 244.648407 118.867787 \r\nL 244.743394 118.703722 \r\nL 244.870042 118.594346 \r\nL 244.974075 118.46674 \r\nL 245.0962 118.357364 \r\nL 245.18214 118.302676 \r\nL 245.408299 118.1933 \r\nL 245.494239 118.065694 \r\nL 245.652549 117.956318 \r\nL 245.747536 117.810483 \r\nL 245.942032 117.701107 \r\nL 246.046065 117.537042 \r\nL 246.326501 117.427666 \r\nL 246.430533 117.208913 \r\nL 246.570751 117.099537 \r\nL 246.665738 116.917243 \r\nL 246.860234 116.826097 \r\nL 246.964267 116.71672 \r\nL 247.1271 116.607344 \r\nL 247.22661 116.479738 \r\nL 247.466338 116.370362 \r\nL 247.543231 116.279215 \r\nL 247.75582 116.169839 \r\nL 247.859853 116.078692 \r\nL 248.086011 115.969316 \r\nL 248.190044 115.878169 \r\nL 248.402632 115.768793 \r\nL 248.497619 115.677646 \r\nL 248.628791 115.56827 \r\nL 248.737346 115.495352 \r\nL 248.868518 115.385976 \r\nL 248.972551 115.2766 \r\nL 249.221325 115.167223 \r\nL 249.311788 115.076076 \r\nL 249.42939 114.9667 \r\nL 249.510807 114.857324 \r\nL 249.682688 114.766177 \r\nL 249.773151 114.638571 \r\nL 249.9586 114.547425 \r\nL 250.067156 114.438048 \r\nL 250.22999 114.328672 \r\nL 250.284268 114.292213 \r\nL 250.704922 114.182837 \r\nL 250.736585 114.10992 \r\nL 251.184378 114.000543 \r\nL 251.28841 113.891167 \r\nL 251.510045 113.781791 \r\nL 251.564323 113.708873 \r\nL 251.73168 113.599497 \r\nL 251.840236 113.490121 \r\nL 251.975931 113.380744 \r\nL 252.052825 113.289598 \r\nL 252.224705 113.180221 \r\nL 252.328738 113.052616 \r\nL 252.514188 112.943239 \r\nL 252.61822 112.870322 \r\nL 252.961981 112.760946 \r\nL 253.056967 112.63334 \r\nL 253.296695 112.523964 \r\nL 253.400728 112.432817 \r\nL 253.536422 112.323441 \r\nL 253.635932 112.141147 \r\nL 253.758057 112.05 \r\nL 253.839474 111.958853 \r\nL 254.124434 111.849477 \r\nL 254.174188 111.794789 \r\nL 254.300837 111.685412 \r\nL 254.400347 111.630724 \r\nL 254.567704 111.521348 \r\nL 254.66269 111.448431 \r\nL 254.816478 111.339054 \r\nL 254.911464 111.229678 \r\nL 255.051682 111.120302 \r\nL 255.160238 111.010926 \r\nL 255.309502 110.901549 \r\nL 255.413535 110.755714 \r\nL 255.485906 110.701026 \r\nL 255.540184 110.500503 \r\nL 255.72111 110.391127 \r\nL 255.829666 110.29998 \r\nL 255.942745 110.190604 \r\nL 256.010593 110.062998 \r\nL 256.137241 109.971851 \r\nL 256.241274 109.862475 \r\nL 256.535279 109.753099 \r\nL 256.575988 109.625493 \r\nL 256.797623 109.516117 \r\nL 256.847378 109.42497 \r\nL 257.200184 109.315594 \r\nL 257.286125 109.187988 \r\nL 257.462528 109.078612 \r\nL 257.557514 108.896318 \r\nL 257.702256 108.805171 \r\nL 257.792719 108.695795 \r\nL 258.190757 108.586419 \r\nL 258.285744 108.477042 \r\nL 258.489286 108.367666 \r\nL 258.579749 108.221831 \r\nL 258.891847 108.112455 \r\nL 258.977787 108.039537 \r\nL 259.194899 107.930161 \r\nL 259.289886 107.820785 \r\nL 259.719586 107.711408 \r\nL 259.819096 107.583803 \r\nL 260.022638 107.492656 \r\nL 260.117625 107.419738 \r\nL 260.352829 107.310362 \r\nL 260.461385 107.200986 \r\nL 260.746344 107.09161 \r\nL 260.836807 106.982233 \r\nL 261.049396 106.872857 \r\nL 261.135336 106.745252 \r\nL 261.343402 106.635875 \r\nL 261.429342 106.544728 \r\nL 261.650977 106.435352 \r\nL 261.75501 106.344205 \r\nL 262.058061 106.234829 \r\nL 262.125909 106.143682 \r\nL 262.257081 106.034306 \r\nL 262.361113 105.833783 \r\nL 262.560133 105.724406 \r\nL 262.62798 105.651489 \r\nL 262.836045 105.542113 \r\nL 262.926509 105.450966 \r\nL 263.080296 105.359819 \r\nL 263.111958 105.286901 \r\nL 263.360732 105.177525 \r\nL 263.437626 105.04992 \r\nL 263.632122 104.940543 \r\nL 263.731632 104.867626 \r\nL 263.908035 104.758249 \r\nL 263.980406 104.648873 \r\nL 264.206564 104.557726 \r\nL 264.31512 104.44835 \r\nL 264.645311 104.338974 \r\nL 264.753867 104.193139 \r\nL 264.934793 104.083763 \r\nL 265.038826 103.974386 \r\nL 265.364494 103.86501 \r\nL 265.409725 103.792093 \r\nL 265.649453 103.700946 \r\nL 265.753486 103.518652 \r\nL 265.997736 103.409276 \r\nL 266.0882 103.299899 \r\nL 266.255557 103.226982 \r\nL 266.350543 103.135835 \r\nL 266.585748 103.026459 \r\nL 266.694303 102.971771 \r\nL 266.965693 102.862394 \r\nL 267.074249 102.789477 \r\nL 267.241606 102.680101 \r\nL 267.341116 102.570724 \r\nL 267.562751 102.461348 \r\nL 267.630598 102.333742 \r\nL 268.010544 102.224366 \r\nL 268.096484 102.133219 \r\nL 268.173378 102.060302 \r\nL 268.277411 101.786861 \r\nL 268.480953 101.677485 \r\nL 268.589509 101.568109 \r\nL 268.883514 101.458732 \r\nL 268.951362 101.385815 \r\nL 269.204659 101.276439 \r\nL 269.27703 101.167062 \r\nL 269.462479 101.057686 \r\nL 269.516757 101.021227 \r\nL 269.788147 100.93008 \r\nL 269.883133 100.838934 \r\nL 270.077629 100.729557 \r\nL 270.122861 100.65664 \r\nL 270.380681 100.565493 \r\nL 270.475668 100.401429 \r\nL 270.624932 100.292052 \r\nL 270.719919 100.182676 \r\nL 270.873706 100.0733 \r\nL 270.896322 100.036841 \r\nL 271.185804 99.927465 \r\nL 271.29436 99.872777 \r\nL 271.46624 99.7634 \r\nL 271.556704 99.708712 \r\nL 271.701445 99.599336 \r\nL 271.796431 99.544648 \r\nL 271.963788 99.435272 \r\nL 272.049728 99.271207 \r\nL 272.36635 99.161831 \r\nL 272.456813 99.088913 \r\nL 272.682971 98.979537 \r\nL 272.759865 98.88839 \r\nL 272.976977 98.779014 \r\nL 273.049347 98.687867 \r\nL 273.203135 98.578491 \r\nL 273.293598 98.505573 \r\nL 273.497141 98.396197 \r\nL 273.601173 98.341509 \r\nL 273.7821 98.232133 \r\nL 273.831855 98.177445 \r\nL 274.035397 98.068068 \r\nL 274.116814 97.976922 \r\nL 274.29774 97.867545 \r\nL 274.388204 97.776398 \r\nL 274.854089 97.667022 \r\nL 274.854089 97.648793 \r\nL 275.080248 97.539416 \r\nL 275.134526 97.484728 \r\nL 275.487332 97.375352 \r\nL 275.528041 97.302435 \r\nL 275.749676 97.193058 \r\nL 275.853709 97.047223 \r\nL 275.993927 96.956076 \r\nL 276.066297 96.810241 \r\nL 276.315071 96.700865 \r\nL 276.423627 96.57326 \r\nL 276.631693 96.463883 \r\nL 276.722156 96.354507 \r\nL 276.966407 96.245131 \r\nL 277.070439 96.135755 \r\nL 277.269459 96.026378 \r\nL 277.301121 95.98992 \r\nL 277.531802 95.880543 \r\nL 277.635835 95.825855 \r\nL 277.988641 95.734708 \r\nL 278.002211 95.661791 \r\nL 278.404772 95.552414 \r\nL 278.486189 95.479497 \r\nL 278.73044 95.370121 \r\nL 278.820903 95.206056 \r\nL 279.137525 95.114909 \r\nL 279.237034 95.060221 \r\nL 279.399868 94.950845 \r\nL 279.508424 94.841469 \r\nL 279.730059 94.732093 \r\nL 279.784337 94.640946 \r\nL 280.155236 94.531569 \r\nL 280.259269 94.476881 \r\nL 280.449242 94.367505 \r\nL 280.449242 94.349276 \r\nL 280.770387 94.239899 \r\nL 280.815618 94.185211 \r\nL 281.068915 94.075835 \r\nL 281.163902 93.93 \r\nL 281.381014 93.820624 \r\nL 281.435292 93.674789 \r\nL 281.91927 93.565412 \r\nL 281.950932 93.492495 \r\nL 282.394202 93.383119 \r\nL 282.502758 93.291972 \r\nL 282.823903 93.182596 \r\nL 282.900796 93.109678 \r\nL 283.122431 93.000302 \r\nL 283.230987 92.909155 \r\nL 283.502377 92.799779 \r\nL 283.59284 92.708632 \r\nL 283.918508 92.599256 \r\nL 284.022541 92.562797 \r\nL 284.090388 92.453421 \r\nL 284.158236 92.380503 \r\nL 284.302977 92.271127 \r\nL 284.384394 92.17998 \r\nL 284.682923 92.070604 \r\nL 284.786955 91.997686 \r\nL 285.00859 91.88831 \r\nL 285.103577 91.778934 \r\nL 285.361397 91.669557 \r\nL 285.420198 91.614869 \r\nL 285.840852 91.505493 \r\nL 285.854422 91.469034 \r\nL 286.130335 91.359658 \r\nL 286.229844 91.268511 \r\nL 286.410771 91.159135 \r\nL 286.483141 91.049759 \r\nL 286.727392 90.958612 \r\nL 286.831425 90.849235 \r\nL 286.985213 90.776318 \r\nL 287.075676 90.666942 \r\nL 287.252079 90.557565 \r\nL 287.252079 90.539336 \r\nL 287.523469 90.42996 \r\nL 287.627502 90.338813 \r\nL 287.849137 90.229437 \r\nL 287.894368 90.13829 \r\nL 288.192897 90.028913 \r\nL 288.269791 89.955996 \r\nL 288.432625 89.864849 \r\nL 288.532134 89.737243 \r\nL 288.758292 89.627867 \r\nL 288.762816 89.591408 \r\nL 289.052298 89.482032 \r\nL 289.160854 89.390885 \r\nL 289.323688 89.281509 \r\nL 289.427721 89.208592 \r\nL 289.590554 89.099215 \r\nL 289.671971 89.008068 \r\nL 289.893606 88.898692 \r\nL 290.002162 88.771087 \r\nL 290.287122 88.66171 \r\nL 290.287122 88.643481 \r\nL 290.648975 88.534105 \r\nL 290.680637 88.479416 \r\nL 290.915841 88.37004 \r\nL 291.024397 88.278893 \r\nL 291.178185 88.187746 \r\nL 291.259602 88.114829 \r\nL 291.440528 88.005453 \r\nL 291.540038 87.950765 \r\nL 291.761673 87.841388 \r\nL 291.775242 87.80493 \r\nL 292.109956 87.695553 \r\nL 292.218512 87.549718 \r\nL 292.453717 87.440342 \r\nL 292.535134 87.349195 \r\nL 292.792954 87.239819 \r\nL 292.88794 87.112213 \r\nL 293.231701 87.021066 \r\nL 293.249793 86.966378 \r\nL 293.51666 86.875231 \r\nL 293.584507 86.802314 \r\nL 293.779003 86.692938 \r\nL 293.779003 86.638249 \r\nL 294.095625 86.528873 \r\nL 294.172519 86.474185 \r\nL 294.412246 86.364809 \r\nL 294.462001 86.291891 \r\nL 294.774099 86.182515 \r\nL 294.878132 86.109598 \r\nL 295.040966 86.000221 \r\nL 295.040966 85.981992 \r\nL 295.230939 85.872616 \r\nL 295.230939 85.854386 \r\nL 295.515898 85.74501 \r\nL 295.624454 85.562716 \r\nL 295.841566 85.45334 \r\nL 295.932029 85.343964 \r\nL 296.031539 85.234588 \r\nL 296.085816 85.125211 \r\nL 296.397915 85.015835 \r\nL 296.474808 84.942918 \r\nL 296.750721 84.833541 \r\nL 296.818569 84.760624 \r\nL 297.198515 84.651247 \r\nL 297.302547 84.468954 \r\nL 297.623692 84.359577 \r\nL 297.659877 84.28666 \r\nL 297.940313 84.177284 \r\nL 298.008161 84.104366 \r\nL 298.419769 83.99499 \r\nL 298.528324 83.885614 \r\nL 298.790668 83.776237 \r\nL 298.872085 83.685091 \r\nL 299.025872 83.575714 \r\nL 299.098243 83.429879 \r\nL 299.306309 83.320503 \r\nL 299.405818 83.229356 \r\nL 299.586745 83.11998 \r\nL 299.695301 83.083521 \r\nL 299.858134 82.974145 \r\nL 299.939551 82.901227 \r\nL 300.093339 82.791851 \r\nL 300.165709 82.700704 \r\nL 300.432576 82.591328 \r\nL 300.541132 82.554869 \r\nL 300.618026 82.445493 \r\nL 300.631595 82.409034 \r\nL 301.052249 82.299658 \r\nL 301.147236 82.153823 \r\nL 301.432195 82.044447 \r\nL 301.513612 81.93507 \r\nL 301.699062 81.825694 \r\nL 301.807618 81.771006 \r\nL 302.205656 81.66163 \r\nL 302.314212 81.588712 \r\nL 302.630833 81.479336 \r\nL 302.653449 81.442877 \r\nL 303.223368 81.333501 \r\nL 303.322877 81.187666 \r\nL 303.616883 81.096519 \r\nL 303.725439 80.950684 \r\nL 303.978736 80.841308 \r\nL 304.023967 80.76839 \r\nL 304.268218 80.659014 \r\nL 304.358682 80.604326 \r\nL 304.621025 80.49495 \r\nL 304.652687 80.403803 \r\nL 305.019063 80.312656 \r\nL 305.105003 80.257968 \r\nL 305.417102 80.148592 \r\nL 305.507565 80.075674 \r\nL 305.919173 79.966298 \r\nL 306.023206 79.838692 \r\nL 306.299118 79.747545 \r\nL 306.348873 79.638169 \r\nL 306.520753 79.528793 \r\nL 306.61574 79.437646 \r\nL 306.697157 79.32827 \r\nL 306.774051 79.255352 \r\nL 307.018301 79.164205 \r\nL 307.036394 79.091288 \r\nL 307.461571 78.981911 \r\nL 307.570127 78.817847 \r\nL 307.805332 78.708471 \r\nL 307.909364 78.672012 \r\nL 308.099337 78.562636 \r\nL 308.207893 78.507948 \r\nL 308.492853 78.398571 \r\nL 308.578793 78.289195 \r\nL 308.768765 78.179819 \r\nL 308.868275 78.070443 \r\nL 309.108003 77.961066 \r\nL 309.198466 77.888149 \r\nL 309.573888 77.797002 \r\nL 309.63269 77.724085 \r\nL 309.863371 77.614708 \r\nL 309.96288 77.56002 \r\nL 310.139284 77.450644 \r\nL 310.139284 77.432414 \r\nL 310.392581 77.323038 \r\nL 310.40615 77.286579 \r\nL 310.799666 77.177203 \r\nL 310.872036 77.086056 \r\nL 311.03487 76.97668 \r\nL 311.093671 76.903763 \r\nL 311.288167 76.794386 \r\nL 311.310783 76.757928 \r\nL 311.460047 76.648551 \r\nL 311.550511 76.593863 \r\nL 311.817377 76.484487 \r\nL 311.925933 76.338652 \r\nL 312.355634 76.229276 \r\nL 312.437051 76.10167 \r\nL 312.676778 76.010523 \r\nL 312.776288 75.919376 \r\nL 312.916506 75.846459 \r\nL 313.002446 75.682394 \r\nL 313.228604 75.573018 \r\nL 313.319067 75.500101 \r\nL 313.631166 75.390724 \r\nL 313.671874 75.336036 \r\nL 313.816615 75.22666 \r\nL 313.870893 75.171972 \r\nL 314.164899 75.062596 \r\nL 314.228223 74.93499 \r\nL 314.531275 74.843843 \r\nL 314.603646 74.716237 \r\nL 314.730294 74.606861 \r\nL 314.793619 74.533944 \r\nL 314.951929 74.424567 \r\nL 315.019777 74.388109 \r\nL 315.182611 74.278732 \r\nL 315.273074 74.187586 \r\nL 315.512801 74.078209 \r\nL 315.580649 73.968833 \r\nL 315.879178 73.859457 \r\nL 315.969641 73.713622 \r\nL 316.222938 73.604245 \r\nL 316.317924 73.494869 \r\nL 316.557652 73.385493 \r\nL 316.657162 73.330805 \r\nL 316.856181 73.221429 \r\nL 316.924028 73.16674 \r\nL 317.231603 73.057364 \r\nL 317.317543 72.984447 \r\nL 317.787952 72.87507 \r\nL 317.891985 72.820382 \r\nL 318.208607 72.711006 \r\nL 318.312639 72.656318 \r\nL 318.534274 72.546942 \r\nL 318.629261 72.474024 \r\nL 319.004683 72.364648 \r\nL 319.058961 72.255272 \r\nL 319.384629 72.145895 \r\nL 319.420814 72.091207 \r\nL 319.669588 71.981831 \r\nL 319.719343 71.854225 \r\nL 320.149043 71.744849 \r\nL 320.185229 71.690161 \r\nL 320.750624 71.580785 \r\nL 320.854657 71.489638 \r\nL 321.184848 71.380262 \r\nL 321.279834 71.307344 \r\nL 321.632641 71.197968 \r\nL 321.695965 71.161509 \r\nL 322.053295 71.052133 \r\nL 322.152805 70.997445 \r\nL 322.401579 70.888068 \r\nL 322.469426 70.760463 \r\nL 322.871988 70.651087 \r\nL 322.97602 70.596398 \r\nL 323.152424 70.487022 \r\nL 323.220271 70.414105 \r\nL 323.455476 70.304728 \r\nL 323.455476 70.286499 \r\nL 323.889699 70.177123 \r\nL 323.975639 70.104205 \r\nL 324.197274 69.994829 \r\nL 324.265122 69.885453 \r\nL 324.531988 69.776076 \r\nL 324.545558 69.721388 \r\nL 324.821471 69.612012 \r\nL 324.875749 69.557324 \r\nL 325.101907 69.447948 \r\nL 325.210463 69.320342 \r\nL 325.522561 69.210966 \r\nL 325.599455 69.10159 \r\nL 325.870845 68.992213 \r\nL 325.961308 68.882837 \r\nL 326.341254 68.773461 \r\nL 326.445286 68.700543 \r\nL 326.703107 68.591167 \r\nL 326.739292 68.518249 \r\nL 327.05139 68.408873 \r\nL 327.087575 68.354185 \r\nL 327.417766 68.263038 \r\nL 327.440382 68.20835 \r\nL 327.933407 68.098974 \r\nL 328.02387 67.953139 \r\nL 328.322399 67.861992 \r\nL 328.408339 67.770845 \r\nL 328.634497 67.661469 \r\nL 328.720437 67.552093 \r\nL 328.933026 67.442716 \r\nL 328.987304 67.351569 \r\nL 329.258694 67.242193 \r\nL 329.28131 67.187505 \r\nL 329.602454 67.078129 \r\nL 329.71101 66.968753 \r\nL 330.280929 66.859376 \r\nL 330.317114 66.804688 \r\nL 330.565888 66.695312 \r\nL 330.633735 66.585936 \r\nL 330.896079 66.476559 \r\nL 330.950357 66.421871 \r\nL 331.330302 66.330724 \r\nL 331.407196 66.239577 \r\nL 331.637877 66.130201 \r\nL 331.732864 66.057284 \r\nL 331.954499 65.947907 \r\nL 332.044962 65.87499 \r\nL 332.289213 65.783843 \r\nL 332.384199 65.674467 \r\nL 332.678205 65.565091 \r\nL 332.737006 65.510402 \r\nL 333.058151 65.401026 \r\nL 333.166707 65.328109 \r\nL 333.42905 65.236962 \r\nL 333.492374 65.127586 \r\nL 333.727579 65.036439 \r\nL 333.831611 64.927062 \r\nL 334.075862 64.817686 \r\nL 334.170849 64.70831 \r\nL 334.641258 64.598934 \r\nL 334.722675 64.507787 \r\nL 334.93074 64.39841 \r\nL 335.021203 64.343722 \r\nL 335.392103 64.252575 \r\nL 335.47352 64.161429 \r\nL 335.83085 64.052052 \r\nL 335.90322 63.997364 \r\nL 336.26055 63.887988 \r\nL 336.36006 63.742153 \r\nL 336.69025 63.632777 \r\nL 336.776191 63.596318 \r\nL 337.079242 63.505171 \r\nL 337.156136 63.450483 \r\nL 337.41848 63.341107 \r\nL 337.41848 63.322877 \r\nL 337.811995 63.213501 \r\nL 337.920551 63.085895 \r\nL 338.273358 62.976519 \r\nL 338.372867 62.848913 \r\nL 338.603548 62.739537 \r\nL 338.694012 62.64839 \r\nL 338.915647 62.575473 \r\nL 338.988017 62.466097 \r\nL 339.182513 62.35672 \r\nL 339.254884 62.283803 \r\nL 339.422241 62.174427 \r\nL 339.52175 62.119738 \r\nL 339.928835 62.010362 \r\nL 340.019298 61.900986 \r\nL 340.123331 61.79161 \r\nL 340.123331 61.77338 \r\nL 340.485184 61.664004 \r\nL 340.534939 61.609316 \r\nL 340.914885 61.49994 \r\nL 341.023441 61.445252 \r\nL 341.331016 61.335875 \r\nL 341.412433 61.299416 \r\nL 341.747147 61.19004 \r\nL 341.828564 61.044205 \r\nL 342.235648 60.934829 \r\nL 342.339681 60.861911 \r\nL 342.846275 60.752535 \r\nL 342.932215 60.679618 \r\nL 343.185513 60.588471 \r\nL 343.262406 60.533783 \r\nL 343.547366 60.424406 \r\nL 343.637829 60.369718 \r\nL 344.026821 60.260342 \r\nL 344.099191 60.132736 \r\nL 344.429382 60.04159 \r\nL 344.501753 59.950443 \r\nL 344.800282 59.841066 \r\nL 344.863606 59.74992 \r\nL 345.11238 59.640543 \r\nL 345.130473 59.585855 \r\nL 345.492326 59.476479 \r\nL 345.600882 59.367103 \r\nL 345.926549 59.257726 \r\nL 346.035105 59.14835 \r\nL 346.415051 59.038974 \r\nL 346.519084 58.984286 \r\nL 346.763334 58.874909 \r\nL 346.867367 58.765533 \r\nL 347.32873 58.656157 \r\nL 347.419193 58.528551 \r\nL 347.645351 58.419175 \r\nL 347.663444 58.364487 \r\nL 347.984588 58.255111 \r\nL 348.056959 58.200423 \r\nL 348.283117 58.091046 \r\nL 348.346441 57.999899 \r\nL 348.649493 57.890523 \r\nL 348.649493 57.872294 \r\nL 349.115379 57.762918 \r\nL 349.223935 57.708229 \r\nL 349.463663 57.598853 \r\nL 349.572219 57.544165 \r\nL 349.680775 57.434789 \r\nL 349.771238 57.343642 \r\nL 349.943118 57.234266 \r\nL 350.033581 57.124889 \r\nL 350.264263 57.015513 \r\nL 350.264263 56.997284 \r\nL 350.852274 56.887907 \r\nL 350.929168 56.833219 \r\nL 351.028677 56.723843 \r\nL 351.13271 56.650926 \r\nL 351.340775 56.541549 \r\nL 351.413146 56.505091 \r\nL 351.666443 56.395714 \r\nL 351.770476 56.304567 \r\nL 352.069005 56.195191 \r\nL 352.168514 56.049356 \r\nL 352.36301 55.93998 \r\nL 352.457997 55.794145 \r\nL 352.711294 55.684769 \r\nL 352.81985 55.63008 \r\nL 353.068624 55.520704 \r\nL 353.086716 55.484245 \r\nL 353.466662 55.374869 \r\nL 353.575218 55.320181 \r\nL 353.796853 55.210805 \r\nL 353.801376 55.174346 \r\nL 354.045627 55.06497 \r\nL 354.108951 54.992052 \r\nL 354.47985 54.882676 \r\nL 354.583883 54.736841 \r\nL 354.941213 54.627465 \r\nL 355.045246 54.518089 \r\nL 355.316636 54.426942 \r\nL 355.393529 54.317565 \r\nL 355.664919 54.208189 \r\nL 355.768952 54.135272 \r\nL 356.216745 54.025895 \r\nL 356.320778 53.971207 \r\nL 356.587644 53.861831 \r\nL 356.587644 53.843602 \r\nL 357.098762 53.734225 \r\nL 357.166609 53.679537 \r\nL 357.343013 53.58839 \r\nL 357.343013 53.551932 \r\nL 357.646065 53.442555 \r\nL 357.646065 53.387867 \r\nL 358.306446 53.29672 \r\nL 358.38334 53.169115 \r\nL 358.822087 53.077968 \r\nL 358.92612 52.986821 \r\nL 359.545793 52.877445 \r\nL 359.649826 52.804527 \r\nL 359.880507 52.695151 \r\nL 359.97097 52.622233 \r\nL 360.387101 52.512857 \r\nL 360.436856 52.43994 \r\nL 360.721815 52.330563 \r\nL 360.798709 52.239416 \r\nL 361.31435 52.13004 \r\nL 361.38672 52.038893 \r\nL 361.870699 51.929517 \r\nL 361.91593 51.874829 \r\nL 362.336585 51.765453 \r\nL 362.408955 51.728994 \r\nL 362.666775 51.619618 \r\nL 362.684868 51.583159 \r\nL 363.128138 51.473783 \r\nL 363.128138 51.455553 \r\nL 363.304541 51.346177 \r\nL 363.381435 51.25503 \r\nL 364.037294 51.145654 \r\nL 364.14585 51.054507 \r\nL 364.408193 50.945131 \r\nL 364.471517 50.872213 \r\nL 364.991681 50.762837 \r\nL 365.050482 50.726378 \r\nL 365.457567 50.617002 \r\nL 365.484706 50.562314 \r\nL 365.959638 50.452938 \r\nL 366.059148 50.416479 \r\nL 366.52051 50.307103 \r\nL 366.52051 50.288873 \r\nL 366.832609 50.179497 \r\nL 366.936641 50.070121 \r\nL 367.398004 49.960744 \r\nL 367.488467 49.887827 \r\nL 367.714625 49.778451 \r\nL 367.818658 49.705533 \r\nL 368.076478 49.596157 \r\nL 368.076478 49.577928 \r\nL 368.488086 49.468551 \r\nL 368.583073 49.413863 \r\nL 368.967541 49.304487 \r\nL 369.071574 49.249799 \r\nL 369.419858 49.140423 \r\nL 369.492228 49.103964 \r\nL 369.786234 48.994588 \r\nL 369.786234 48.976358 \r\nL 370.283782 48.866982 \r\nL 370.356152 48.775835 \r\nL 370.944164 48.666459 \r\nL 371.03915 48.611771 \r\nL 371.405526 48.520624 \r\nL 371.509559 48.393018 \r\nL 371.93926 48.283642 \r\nL 372.047815 48.156036 \r\nL 372.251358 48.04666 \r\nL 372.251358 48.028431 \r\nL 372.721767 47.919054 \r\nL 372.807707 47.864366 \r\nL 373.16956 47.75499 \r\nL 373.2555 47.663843 \r\nL 373.69877 47.554467 \r\nL 373.69877 47.536237 \r\nL 374.309397 47.426861 \r\nL 374.345582 47.353944 \r\nL 374.960732 47.244567 \r\nL 374.974302 47.189879 \r\nL 375.38591 47.080503 \r\nL 375.480896 47.007586 \r\nL 375.761332 46.898209 \r\nL 375.865365 46.825292 \r\nL 376.109616 46.715915 \r\nL 376.141278 46.661227 \r\nL 376.557409 46.551851 \r\nL 376.61621 46.497163 \r\nL 377.091142 46.387787 \r\nL 377.168036 46.333099 \r\nL 377.620352 46.223722 \r\nL 377.719862 46.169034 \r\nL 377.959589 46.059658 \r\nL 377.959589 46.041429 \r\nL 378.393813 45.932052 \r\nL 378.497846 45.822676 \r\nL 378.941116 45.7133 \r\nL 378.972778 45.658612 \r\nL 379.307492 45.549235 \r\nL 379.307492 45.512777 \r\nL 379.872887 45.4034 \r\nL 379.981443 45.294024 \r\nL 380.198555 45.184648 \r\nL 380.198555 45.166419 \r\nL 380.492561 45.075272 \r\nL 380.497084 45.020584 \r\nL 380.718719 44.911207 \r\nL 380.718719 44.892978 \r\nL 381.229836 44.783602 \r\nL 381.284114 44.728913 \r\nL 381.768093 44.619537 \r\nL 381.790708 44.564849 \r\nL 382.066621 44.455473 \r\nL 382.170654 44.382555 \r\nL 382.496322 44.273179 \r\nL 382.582262 44.218491 \r\nL 382.853652 44.127344 \r\nL 382.948638 44.054427 \r\nL 383.287875 43.94505 \r\nL 383.346677 43.853903 \r\nL 383.821609 43.744527 \r\nL 383.853271 43.67161 \r\nL 384.337249 43.562233 \r\nL 384.364388 43.525775 \r\nL 384.884552 43.416398 \r\nL 384.920737 43.36171 \r\nL 385.241882 43.252334 \r\nL 385.341391 43.142958 \r\nL 385.603735 43.033581 \r\nL 385.698721 42.997123 \r\nL 386.065097 42.887746 \r\nL 386.151038 42.833058 \r\nL 386.79785 42.723682 \r\nL 386.879267 42.687223 \r\nL 387.372292 42.577847 \r\nL 387.471801 42.541388 \r\nL 387.811038 42.432012 \r\nL 387.910548 42.359095 \r\nL 388.308586 42.249718 \r\nL 388.390003 42.176801 \r\nL 388.738287 42.067425 \r\nL 388.760903 42.012736 \r\nL 389.27202 41.90336 \r\nL 389.380576 41.830443 \r\nL 389.579595 41.721066 \r\nL 389.624827 41.666378 \r\nL 390.090713 41.557002 \r\nL 390.194745 41.484085 \r\nL 390.407334 41.374708 \r\nL 390.488751 41.32002 \r\nL 390.94559 41.210644 \r\nL 391.054146 41.174185 \r\nL 391.21698 41.064809 \r\nL 391.262212 41.010121 \r\nL 391.890931 40.900744 \r\nL 391.913547 40.846056 \r\nL 392.478943 40.754909 \r\nL 392.587498 40.609074 \r\nL 393.211695 40.499698 \r\nL 393.211695 40.481469 \r\nL 393.994202 40.372093 \r\nL 394.043957 40.262716 \r\nL 394.618399 40.15334 \r\nL 394.668153 40.080423 \r\nL 395.143086 39.971046 \r\nL 395.143086 39.952817 \r\nL 395.577309 39.843441 \r\nL 395.658726 39.806982 \r\nL 396.106519 39.697606 \r\nL 396.106519 39.661147 \r\nL 396.617637 39.551771 \r\nL 396.712623 39.515312 \r\nL 396.970443 39.405936 \r\nL 397.006629 39.351247 \r\nL 397.300634 39.241871 \r\nL 397.404667 39.187183 \r\nL 398.087665 39.077807 \r\nL 398.191697 39.041348 \r\nL 398.589736 38.931972 \r\nL 398.689245 38.895513 \r\nL 399.150608 38.786137 \r\nL 399.150608 38.767907 \r\nL 399.978347 38.658531 \r\nL 400.086903 38.603843 \r\nL 400.41257 38.494467 \r\nL 400.457802 38.458008 \r\nL 400.901072 38.348632 \r\nL 400.964396 38.312173 \r\nL 401.1408 38.221026 \r\nL 401.190554 38.148109 \r\nL 401.58407 38.038732 \r\nL 401.633824 37.984044 \r\nL 402.235405 37.874668 \r\nL 402.303253 37.838209 \r\nL 402.746523 37.728833 \r\nL 402.841509 37.637686 \r\nL 403.366196 37.52831 \r\nL 403.402381 37.437163 \r\nL 404.139657 37.327787 \r\nL 404.193935 37.273099 \r\nL 404.709575 37.163722 \r\nL 404.754807 37.109034 \r\nL 405.107614 36.999658 \r\nL 405.152845 36.94497 \r\nL 405.682055 36.835594 \r\nL 405.727287 36.799135 \r\nL 406.116279 36.689759 \r\nL 406.138895 36.6533 \r\nL 406.731429 36.562153 \r\nL 406.731429 36.525694 \r\nL 407.070666 36.416318 \r\nL 407.174699 36.36163 \r\nL 407.482274 36.252254 \r\nL 407.495844 36.215795 \r\nL 407.94816 36.106419 \r\nL 408.04767 36.06996 \r\nL 408.888978 35.960584 \r\nL 408.888978 35.942354 \r\nL 409.70767 35.832978 \r\nL 409.752902 35.796519 \r\nL 410.544455 35.687143 \r\nL 410.630396 35.595996 \r\nL 411.010341 35.504849 \r\nL 411.064619 35.450161 \r\nL 411.860696 35.340785 \r\nL 411.955682 35.286097 \r\nL 412.317535 35.17672 \r\nL 412.426091 35.122032 \r\nL 412.869361 35.012656 \r\nL 412.941732 34.957968 \r\nL 413.158844 34.848592 \r\nL 413.249307 34.702757 \r\nL 413.692577 34.61161 \r\nL 413.742332 34.556922 \r\nL 414.362005 34.465775 \r\nL 414.452468 34.374628 \r\nL 414.678626 34.283481 \r\nL 414.764567 34.192334 \r\nL 415.031433 34.082958 \r\nL 415.063095 34.046499 \r\nL 415.660153 33.937123 \r\nL 415.737047 33.882435 \r\nL 416.551216 33.773058 \r\nL 416.605494 33.7366 \r\nL 417.039718 33.627223 \r\nL 417.112088 33.572535 \r\nL 418.161462 33.463159 \r\nL 418.197647 33.4267 \r\nL 418.482606 33.317324 \r\nL 418.514269 33.280865 \r\nL 419.034432 33.171489 \r\nL 419.124896 33.116801 \r\nL 419.559119 33.025654 \r\nL 419.61792 32.970966 \r\nL 420.386858 32.86159 \r\nL 420.481845 32.752213 \r\nL 421.223643 32.642837 \r\nL 421.223643 32.624608 \r\nL 421.685006 32.515231 \r\nL 421.7619 32.478773 \r\nL 422.322772 32.369396 \r\nL 422.322772 32.351167 \r\nL 422.729857 32.241791 \r\nL 422.797704 32.168873 \r\nL 423.412854 32.059497 \r\nL 423.498794 32.023038 \r\nL 423.86517 31.931891 \r\nL 423.973726 31.877203 \r\nL 424.231547 31.767827 \r\nL 424.281301 31.694909 \r\nL 424.805988 31.585533 \r\nL 424.910021 31.512616 \r\nL 425.434708 31.403239 \r\nL 425.434708 31.38501 \r\nL 425.941302 31.275634 \r\nL 425.941302 31.257404 \r\nL 426.52479 31.148028 \r\nL 426.560976 31.09334 \r\nL 427.022338 30.983964 \r\nL 427.085662 30.929276 \r\nL 427.379668 30.819899 \r\nL 427.452039 30.783441 \r\nL 427.94054 30.674064 \r\nL 427.94054 30.655835 \r\nL 428.632584 30.546459 \r\nL 428.6552 30.51 \r\nL 429.333674 30.400624 \r\nL 429.378906 30.364165 \r\nL 429.921686 30.254789 \r\nL 429.994056 30.21833 \r\nL 430.568498 30.108954 \r\nL 430.618253 30.072495 \r\nL 431.219833 29.963119 \r\nL 431.292204 29.908431 \r\nL 431.816891 29.799054 \r\nL 431.902831 29.726137 \r\nL 432.251115 29.616761 \r\nL 432.35967 29.543843 \r\nL 433.083377 29.434467 \r\nL 433.083377 29.398008 \r\nL 433.906592 29.288632 \r\nL 433.906592 29.270402 \r\nL 434.747901 29.161026 \r\nL 434.806702 29.124567 \r\nL 435.593732 29.015191 \r\nL 435.675149 28.960503 \r\nL 436.44861 28.851127 \r\nL 436.475749 28.814668 \r\nL 437.24921 28.705292 \r\nL 437.262779 28.650604 \r\nL 438.081472 28.541227 \r\nL 438.099564 28.504769 \r\nL 438.429755 28.395392 \r\nL 438.429755 28.377163 \r\nL 439.402235 28.267787 \r\nL 439.456513 28.194869 \r\nL 439.958584 28.085493 \r\nL 440.030955 28.030805 \r\nL 440.840601 27.921429 \r\nL 440.854171 27.88497 \r\nL 442.034716 27.775594 \r\nL 442.102564 27.720905 \r\nL 443.215262 27.611529 \r\nL 443.310248 27.556841 \r\nL 444.196788 27.447465 \r\nL 444.246543 27.411006 \r\nL 444.811938 27.30163 \r\nL 444.911448 27.246942 \r\nL 445.314009 27.137565 \r\nL 445.327579 27.101107 \r\nL 446.309105 26.99173 \r\nL 446.417661 26.937042 \r\nL 447.629869 26.827666 \r\nL 447.679623 26.791207 \r\nL 448.507362 26.681831 \r\nL 448.507362 26.663602 \r\nL 449.466273 26.554225 \r\nL 449.466273 26.535996 \r\nL 450.040715 26.42662 \r\nL 450.122131 26.371932 \r\nL 450.755374 26.262555 \r\nL 450.755374 26.244326 \r\nL 452.026383 26.13495 \r\nL 452.1078 26.098491 \r\nL 452.514885 25.989115 \r\nL 452.514885 25.970885 \r\nL 453.315485 25.861509 \r\nL 453.315485 25.84328 \r\nL 453.989436 25.733903 \r\nL 454.088945 25.697445 \r\nL 454.328673 25.588068 \r\nL 454.360335 25.53338 \r\nL 455.771562 25.424004 \r\nL 455.771562 25.405775 \r\nL 456.902353 25.296398 \r\nL 456.902353 25.278169 \r\nL 457.996958 25.168793 \r\nL 457.996958 25.150563 \r\nL 458.679956 25.041187 \r\nL 458.711618 25.004728 \r\nL 459.589112 24.895352 \r\nL 459.589112 24.877123 \r\nL 460.661101 24.767746 \r\nL 460.747041 24.713058 \r\nL 461.520502 24.603682 \r\nL 461.552164 24.548994 \r\nL 462.307533 24.439618 \r\nL 462.307533 24.421388 \r\nL 462.931729 24.312012 \r\nL 462.967914 24.275553 \r\nL 463.972056 24.202636 \r\nL 464.080612 24.129718 \r\nL 464.609822 24.020342 \r\nL 464.609822 24.002113 \r\nL 465.641104 23.892736 \r\nL 465.641104 23.874507 \r\nL 466.156744 23.765131 \r\nL 466.165791 23.728672 \r\nL 467.043284 23.619296 \r\nL 467.070423 23.582837 \r\nL 468.431895 23.473461 \r\nL 468.436418 23.418773 \r\nL 469.603394 23.309396 \r\nL 469.603394 23.291167 \r\nL 471.1277 23.181791 \r\nL 471.1277 23.163561 \r\nL 471.973532 23.054185 \r\nL 471.973532 23.035956 \r\nL 473.185739 22.926579 \r\nL 473.185739 22.90835 \r\nL 474.786939 22.798974 \r\nL 474.786939 22.780744 \r\nL 475.877021 22.671368 \r\nL 475.913207 22.634909 \r\nL 477.464652 22.525533 \r\nL 477.478221 22.489074 \r\nL 478.495933 22.379698 \r\nL 478.495933 22.361469 \r\nL 479.120129 22.252093 \r\nL 479.120129 22.233863 \r\nL 479.952391 22.124487 \r\nL 480.029285 22.069799 \r\nL 481.865689 21.960423 \r\nL 481.915444 21.923964 \r\nL 484.656481 21.814588 \r\nL 484.656481 21.796358 \r\nL 486.773321 21.686982 \r\nL 486.773321 21.668753 \r\nL 490.143077 21.559376 \r\nL 490.143077 21.541147 \r\nL 493.35 21.45 \r\nL 493.35 21.45 \r\n\" style=\"fill:none;stroke:#4c72b0;stroke-linecap:round;stroke-width:1.5;\"/>\r\n   </g>\r\n   <g id=\"line2d_14\">\r\n    <path clip-path=\"url(#pbe2946be89)\" d=\"M 46.95 456.33 \r\nL 493.35 21.45 \r\n\" style=\"fill:none;stroke:#c44e52;stroke-dasharray:5.55,2.4;stroke-dashoffset:0;stroke-width:1.5;\"/>\r\n   </g>\r\n   <g id=\"patch_3\">\r\n    <path d=\"M 46.95 456.33 \r\nL 46.95 21.45 \r\n\" style=\"fill:none;stroke:#ffffff;stroke-linecap:square;stroke-linejoin:miter;stroke-width:1.25;\"/>\r\n   </g>\r\n   <g id=\"patch_4\">\r\n    <path d=\"M 493.35 456.33 \r\nL 493.35 21.45 \r\n\" style=\"fill:none;stroke:#ffffff;stroke-linecap:square;stroke-linejoin:miter;stroke-width:1.25;\"/>\r\n   </g>\r\n   <g id=\"patch_5\">\r\n    <path d=\"M 46.95 456.33 \r\nL 493.35 456.33 \r\n\" style=\"fill:none;stroke:#ffffff;stroke-linecap:square;stroke-linejoin:miter;stroke-width:1.25;\"/>\r\n   </g>\r\n   <g id=\"patch_6\">\r\n    <path d=\"M 46.95 21.45 \r\nL 493.35 21.45 \r\n\" style=\"fill:none;stroke:#ffffff;stroke-linecap:square;stroke-linejoin:miter;stroke-width:1.25;\"/>\r\n   </g>\r\n   <g id=\"text_15\">\r\n    <!-- ROC -->\r\n    <g style=\"fill:#262626;\" transform=\"translate(261.15 15.45)scale(0.12 -0.12)\">\r\n     <defs>\r\n      <path d=\"M 46.09375 35.546875 \r\nQ 46.09375 17.1875 40.421875 9.171875 \r\nQ 34.765625 1.171875 24.609375 1.171875 \r\nQ 14.453125 1.171875 8.59375 9.171875 \r\nQ 2.734375 17.1875 2.734375 35.546875 \r\nQ 2.734375 53.90625 8.59375 61.71875 \r\nQ 14.453125 69.53125 24.609375 69.53125 \r\nQ 34.765625 69.53125 40.421875 61.71875 \r\nQ 46.09375 53.90625 46.09375 35.546875 \r\nz\r\nM 36.71875 35.546875 \r\nQ 36.71875 51.953125 33.203125 57.03125 \r\nQ 29.6875 62.109375 24.609375 62.109375 \r\nQ 19.53125 62.109375 15.8125 57.03125 \r\nQ 12.109375 51.953125 12.109375 35.546875 \r\nQ 12.109375 19.140625 15.8125 13.859375 \r\nQ 19.53125 8.59375 24.609375 8.59375 \r\nQ 29.6875 8.59375 33.203125 13.859375 \r\nQ 36.71875 19.140625 36.71875 35.546875 \r\nz\r\n\" id=\"SimHei-79\"/>\r\n      <path d=\"M 46.484375 28.515625 \r\nQ 46.09375 13.671875 40.234375 7.421875 \r\nQ 34.375 1.171875 26.171875 1.171875 \r\nQ 16.796875 1.171875 10.15625 8.78125 \r\nQ 3.515625 16.40625 3.515625 33.203125 \r\nQ 3.515625 51.5625 9.953125 60.546875 \r\nQ 16.40625 69.53125 26.5625 69.53125 \r\nQ 35.15625 69.53125 40.8125 63.078125 \r\nQ 46.484375 56.640625 46.09375 44.921875 \r\nL 37.5 44.921875 \r\nQ 37.5 53.515625 34.765625 57.8125 \r\nQ 32.03125 62.109375 26.5625 62.109375 \r\nQ 20.3125 62.109375 16.59375 55.65625 \r\nQ 12.890625 49.21875 12.890625 33.984375 \r\nQ 12.890625 19.921875 16.59375 14.25 \r\nQ 20.3125 8.59375 26.171875 8.59375 \r\nQ 30.46875 8.59375 33.984375 12.6875 \r\nQ 37.5 16.796875 37.5 28.515625 \r\nz\r\n\" id=\"SimHei-67\"/>\r\n     </defs>\r\n     <use xlink:href=\"#SimHei-82\"/>\r\n     <use x=\"50\" xlink:href=\"#SimHei-79\"/>\r\n     <use x=\"100\" xlink:href=\"#SimHei-67\"/>\r\n    </g>\r\n   </g>\r\n   <g id=\"legend_1\">\r\n    <g id=\"patch_7\">\r\n     <path d=\"M 54.65 44.825 \r\nL 177.85 44.825 \r\nQ 180.05 44.825 180.05 42.625 \r\nL 180.05 29.15 \r\nQ 180.05 26.95 177.85 26.95 \r\nL 54.65 26.95 \r\nQ 52.45 26.95 52.45 29.15 \r\nL 52.45 42.625 \r\nQ 52.45 44.825 54.65 44.825 \r\nz\r\n\" style=\"fill:#eaeaf2;opacity:0.8;stroke:#cccccc;stroke-linejoin:miter;\"/>\r\n    </g>\r\n    <g id=\"line2d_15\">\r\n     <path d=\"M 56.85 35.2 \r\nL 78.85 35.2 \r\n\" style=\"fill:none;stroke:#4c72b0;stroke-linecap:round;stroke-width:1.5;\"/>\r\n    </g>\r\n    <g id=\"line2d_16\"/>\r\n    <g id=\"text_16\">\r\n     <!-- Val AUC = 0.7351 -->\r\n     <g style=\"fill:#262626;\" transform=\"translate(87.65 39.05)scale(0.11 -0.11)\">\r\n      <defs>\r\n       <path d=\"M 47.65625 68.75 \r\nL 28.125 1.171875 \r\nL 20.3125 1.171875 \r\nL 0.78125 68.75 \r\nL 10.15625 68.75 \r\nL 23.828125 17.578125 \r\nL 24.609375 17.578125 \r\nL 38.28125 68.75 \r\nz\r\n\" id=\"SimHei-86\"/>\r\n       <path d=\"M 48.046875 1.953125 \r\nL 38.671875 1.953125 \r\nL 33.203125 22.65625 \r\nL 16.015625 22.65625 \r\nL 10.546875 1.953125 \r\nL 1.171875 1.953125 \r\nL 20.703125 69.53125 \r\nL 28.515625 69.53125 \r\nz\r\nM 31.25 30.078125 \r\nL 25 53.90625 \r\nL 24.21875 53.90625 \r\nL 17.96875 30.078125 \r\nz\r\n\" id=\"SimHei-65\"/>\r\n       <path d=\"M 44.921875 21.484375 \r\nQ 44.921875 12.109375 40.03125 6.640625 \r\nQ 35.15625 1.171875 24.609375 1.171875 \r\nQ 14.0625 1.171875 9.171875 6.640625 \r\nQ 4.296875 12.109375 4.296875 21.484375 \r\nL 4.296875 68.75 \r\nL 13.28125 68.75 \r\nL 13.28125 21.484375 \r\nQ 13.28125 14.84375 16.40625 11.71875 \r\nQ 19.53125 8.59375 24.609375 8.59375 \r\nQ 29.6875 8.59375 32.8125 11.71875 \r\nQ 35.9375 14.84375 35.9375 21.484375 \r\nL 35.9375 68.75 \r\nL 44.921875 68.75 \r\nz\r\n\" id=\"SimHei-85\"/>\r\n       <path d=\"M 46.484375 45.3125 \r\nL 1.953125 45.3125 \r\nL 1.953125 51.5625 \r\nL 46.484375 51.5625 \r\nz\r\nM 46.484375 21.484375 \r\nL 1.953125 21.484375 \r\nL 1.953125 27.734375 \r\nL 46.484375 27.734375 \r\nz\r\n\" id=\"SimHei-61\"/>\r\n       <path d=\"M 13.28125 2.34375 \r\nQ 20.3125 32.03125 37.890625 61.328125 \r\nL 4.296875 61.328125 \r\nL 4.296875 68.359375 \r\nL 46.09375 68.359375 \r\nL 46.09375 61.71875 \r\nQ 27.734375 32.03125 21.875 2.34375 \r\nL 13.28125 2.34375 \r\nz\r\n\" id=\"SimHei-55\"/>\r\n       <path d=\"M 3.90625 19.140625 \r\nL 10.9375 20.3125 \r\nQ 12.5 15.234375 16.015625 11.90625 \r\nQ 19.53125 8.59375 24.796875 8.78125 \r\nQ 30.078125 8.984375 33.203125 13.078125 \r\nQ 36.328125 17.1875 35.9375 22.453125 \r\nQ 35.546875 27.734375 31.828125 30.65625 \r\nQ 28.125 33.59375 19.921875 34.765625 \r\nL 19.921875 39.84375 \r\nQ 28.125 40.625 31.828125 44.140625 \r\nQ 35.546875 47.65625 35.15625 53.3125 \r\nQ 34.765625 58.984375 30.078125 61.515625 \r\nQ 25.390625 64.0625 20.109375 62.109375 \r\nQ 14.84375 60.15625 11.71875 51.171875 \r\nL 4.6875 52.34375 \r\nQ 7.03125 59.375 11.125 64.0625 \r\nQ 15.234375 68.75 22.265625 69.53125 \r\nQ 29.296875 70.3125 34.5625 67.765625 \r\nQ 39.84375 65.234375 41.984375 59.953125 \r\nQ 44.140625 54.6875 42.578125 48.4375 \r\nQ 41.015625 42.1875 33.59375 37.5 \r\nQ 39.0625 35.15625 41.984375 30.46875 \r\nQ 44.921875 25.78125 43.9375 18.15625 \r\nQ 42.96875 10.546875 37.109375 5.859375 \r\nQ 31.25 1.171875 23.828125 1.359375 \r\nQ 16.40625 1.5625 10.9375 6.046875 \r\nQ 5.46875 10.546875 3.90625 19.140625 \r\nz\r\n\" id=\"SimHei-51\"/>\r\n       <path d=\"M 8.59375 20.703125 \r\nQ 11.328125 10.15625 17.96875 8.984375 \r\nQ 24.609375 7.8125 28.703125 10.34375 \r\nQ 32.8125 12.890625 34.5625 16.984375 \r\nQ 36.328125 21.09375 36.125 26.171875 \r\nQ 35.9375 31.25 33.390625 34.765625 \r\nQ 30.859375 38.28125 26.953125 39.453125 \r\nQ 23.046875 40.625 18.15625 39.453125 \r\nQ 13.28125 38.28125 10.15625 33.984375 \r\nL 3.515625 34.765625 \r\nQ 4.296875 37.109375 10.9375 68.359375 \r\nL 41.796875 68.359375 \r\nL 41.796875 61.328125 \r\nL 16.796875 61.328125 \r\nQ 14.84375 50.78125 12.890625 44.53125 \r\nQ 18.75 47.265625 23.828125 47.0625 \r\nQ 28.90625 46.875 33.59375 44.71875 \r\nQ 38.28125 42.578125 40.421875 38.859375 \r\nQ 42.578125 35.15625 43.546875 31.4375 \r\nQ 44.53125 27.734375 44.328125 23.4375 \r\nQ 44.140625 19.140625 42.578125 14.640625 \r\nQ 41.015625 10.15625 37.890625 7.21875 \r\nQ 34.765625 4.296875 30.265625 2.53125 \r\nQ 25.78125 0.78125 19.921875 1.171875 \r\nQ 14.0625 1.5625 8.78125 5.46875 \r\nQ 3.515625 9.375 1.5625 18.75 \r\nz\r\n\" id=\"SimHei-53\"/>\r\n      </defs>\r\n      <use xlink:href=\"#SimHei-86\"/>\r\n      <use x=\"50\" xlink:href=\"#SimHei-97\"/>\r\n      <use x=\"100\" xlink:href=\"#SimHei-108\"/>\r\n      <use x=\"150\" xlink:href=\"#SimHei-32\"/>\r\n      <use x=\"200\" xlink:href=\"#SimHei-65\"/>\r\n      <use x=\"250\" xlink:href=\"#SimHei-85\"/>\r\n      <use x=\"300\" xlink:href=\"#SimHei-67\"/>\r\n      <use x=\"350\" xlink:href=\"#SimHei-32\"/>\r\n      <use x=\"400\" xlink:href=\"#SimHei-61\"/>\r\n      <use x=\"450\" xlink:href=\"#SimHei-32\"/>\r\n      <use x=\"500\" xlink:href=\"#SimHei-48\"/>\r\n      <use x=\"550\" xlink:href=\"#SimHei-46\"/>\r\n      <use x=\"600\" xlink:href=\"#SimHei-55\"/>\r\n      <use x=\"650\" xlink:href=\"#SimHei-51\"/>\r\n      <use x=\"700\" xlink:href=\"#SimHei-53\"/>\r\n      <use x=\"750\" xlink:href=\"#SimHei-49\"/>\r\n     </g>\r\n    </g>\r\n   </g>\r\n  </g>\r\n </g>\r\n <defs>\r\n  <clipPath id=\"pbe2946be89\">\r\n   <rect height=\"434.88\" width=\"446.4\" x=\"46.95\" y=\"21.45\"/>\r\n  </clipPath>\r\n </defs>\r\n</svg>\r\n",
      "image/png": "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\n"
     },
     "metadata": {}
    }
   ],
   "source": [
    "base_params_lgb = {\n",
    "                    'boosting_type': 'gbdt',\n",
    "                    'objective': 'binary',\n",
    "                    'metric': 'auc',\n",
    "                    'learning_rate': 0.01,\n",
    "                    'num_leaves': 14,\n",
    "                    'max_depth': 19,\n",
    "                    'min_data_in_leaf': 37,\n",
    "                    'min_child_weight':1.6,\n",
    "                    'bagging_fraction': 0.98,\n",
    "                    'feature_fraction': 0.69,\n",
    "                    'bagging_freq': 96,\n",
    "                    'reg_lambda': 9,\n",
    "                    'reg_alpha': 7,\n",
    "                    'min_split_gain': 0.4,\n",
    "                    'nthread': 8,\n",
    "                    'seed': 2020,\n",
    "                    'silent': True,\n",
    "}\n",
    "\n",
    "\"\"\"使用训练集数据进行模型训练\"\"\"\n",
    "final_model_lgb = lgb.train(base_params_lgb, train_set=train_matrix, valid_sets=valid_matrix, num_boost_round=13000, verbose_eval=1000, early_stopping_rounds=200)\n",
    "\n",
    "\"\"\"预测并计算roc的相关指标\"\"\"\n",
    "val_pre_lgb = final_model_lgb.predict(X_val)\n",
    "fpr, tpr, threshold = metrics.roc_curve(y_val, val_pre_lgb)\n",
    "roc_auc = metrics.auc(fpr, tpr)\n",
    "print('调参后lightgbm单模型在验证集上的AUC：{}'.format(roc_auc))\n",
    "\"\"\"画出roc曲线图\"\"\"\n",
    "plt.figure(figsize=(8, 8))\n",
    "plt.title('Validation ROC')\n",
    "plt.plot(fpr, tpr, 'b', label = 'Val AUC = %0.4f' % roc_auc)\n",
    "plt.ylim(0,1)\n",
    "plt.xlim(0,1)\n",
    "plt.legend(loc='best')\n",
    "plt.title('ROC')\n",
    "plt.ylabel('True Positive Rate')\n",
    "plt.xlabel('False Positive Rate')\n",
    "# 画出对角线\n",
    "plt.plot([0,1],[0,1],'r--')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "\"\"\"保存模型到本地\"\"\"\n",
    "# 保存模型\n",
    "import pickle\n",
    "pickle.dump(final_model_lgb, open('./model_lgb_best.pkl', 'wb'))"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.5-final"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}